Publications | Perceiving Systems - Max Planck Institute for Intelligent Systems

159 results (View BibTeX file of all listed publications)

2014

Omnidirectional 3D Reconstruction in Augmented Manhattan Worlds

Schoenbein, M., Geiger, A.

International Conference on Intelligent Robots and Systems, pages: 716 - 723, IEEE, Chicago, IL, USA, October 2014 (conference)

Abstract

This paper proposes a method for high-quality omnidirectional 3D reconstruction of augmented Manhattan worlds from catadioptric stereo video sequences. In contrast to existing works we do not rely on constructing virtual perspective views, but instead propose to optimize depth jointly in a unified omnidirectional space. Furthermore, we show that plane-based prior models can be applied even though planes in 3D do not project to planes in the omnidirectional domain. Towards this goal, we propose an omnidirectional slanted-plane Markov random field model which relies on plane hypotheses extracted using a novel voting scheme for 3D planes in omnidirectional space. To quantitatively evaluate our method we introduce a dataset which we have captured using our autonomous driving platform AnnieWAY which we equipped with two horizontally aligned catadioptric cameras and a Velodyne HDL-64E laser scanner for precise ground truth depth measurements. As evidenced by our experiments, the proposed method clearly benefits from the unified view and significantly outperforms existing stereo matching techniques both quantitatively and qualitatively. Furthermore, our method is able to reduce noise and the obtained depth maps can be represented very compactly by a small number of image segments and plane parameters.

pdf DOI [BibTex]

2014

Schoenbein, M., Geiger, A. Omnidirectional 3D Reconstruction in Augmented Manhattan Worlds International Conference on Intelligent Robots and Systems, pages: 716 - 723, IEEE, Chicago, IL, USA, October 2014 (conference)

pdf DOI [BibTex]

Image-based 4-d Reconstruction Using 3-d Change Detection

Ulusoy, A. O., Mundy, J. L.

In Computer Vision – ECCV 2014, pages: 31-45, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

This paper describes an approach to reconstruct the complete history of a 3-d scene over time from imagery. The proposed approach avoids rebuilding 3-d models of the scene at each time instant. Instead, the approach employs an initial 3-d model which is continuously updated with changes in the environment to form a full 4-d representation. This updating scheme is enabled by a novel algorithm that infers 3-d changes with respect to the model at one time step from images taken at a subsequent time step. This algorithm can effectively detect changes even when the illumination conditions between image collections are significantly different. The performance of the proposed framework is demonstrated on four challenging datasets in terms of 4-d modeling accuracy as well as quantitative evaluation of 3-d change detection.

video pdf supplementary DOI [BibTex]

Ulusoy, A. O., Mundy, J. L. Image-based 4-d Reconstruction Using 3-d Change Detection In Computer Vision – ECCV 2014, pages: 31-45, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

video pdf supplementary DOI [BibTex]

Human Pose Estimation with Fields of Parts

Kiefel, M., Gehler, P.

In Computer Vision – ECCV 2014, LNCS 8693, pages: 331-346, Lecture Notes in Computer Science, (Editors: Fleet, David and Pajdla, Tomas and Schiele, Bernt and Tuytelaars, Tinne), Springer, September 2014 (inproceedings)

Abstract

This paper proposes a new formulation of the human pose estimation problem. We present the Fields of Parts model, a binary Conditional Random Field model designed to detect human body parts of articulated people in single images. The Fields of Parts model is inspired by the idea of Pictorial Structures, it models local appearance and joint spatial configuration of the human body. However the underlying graph structure is entirely different. The idea is simple: we model the presence and absence of a body part at every possible position, orientation, and scale in an image with a binary random variable. This results into a vast number of random variables, however, we show that approximate inference in this model is efficient. Moreover we can encode the very same appearance and spatial structure as in Pictorial Structures models. This approach allows us to combine ideas from segmentation and pose estimation into a single model. The Fields of Parts model can use evidence from the background, include local color information, and it is connected more densely than a kinematic chain structure. On the challenging Leeds Sports Poses dataset we improve over the Pictorial Structures counterpart by 5.5% in terms of Average Precision of Keypoints (APK).

website pdf DOI Project Page [BibTex]

Kiefel, M., Gehler, P. Human Pose Estimation with Fields of Parts In Computer Vision – ECCV 2014, LNCS 8693, pages: 331-346, Lecture Notes in Computer Science, (Editors: Fleet, David and Pajdla, Tomas and Schiele, Bernt and Tuytelaars, Tinne), Springer, September 2014 (inproceedings)

website pdf DOI Project Page [BibTex]

Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points

Tzionas, D., Srikantha, A., Aponte, P., Gall, J.

In German Conference on Pattern Recognition (GCPR), pages: 1-13, Lecture Notes in Computer Science, Springer, September 2014 (inproceedings)

Abstract

Hand motion capture has been an active research topic in recent years, following the success of full-body pose tracking. Despite similarities, hand tracking proves to be more challenging, characterized by a higher dimensionality, severe occlusions and self-similarity between fingers. For this reason, most approaches rely on strong assumptions, like hands in isolation or expensive multi-camera systems, that limit the practical use. In this work, we propose a framework for hand tracking that can capture the motion of two interacting hands using only a single, inexpensive RGB-D camera. Our approach combines a generative model with collision detection and discriminatively learned salient points. We quantitatively evaluate our approach on 14 new sequences with challenging interactions.

pdf Supplementary pdf Supplementary Material Project Page DOI Project Page [BibTex]

Tzionas, D., Srikantha, A., Aponte, P., Gall, J. Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points In German Conference on Pattern Recognition (GCPR), pages: 1-13, Lecture Notes in Computer Science, Springer, September 2014 (inproceedings)

pdf Supplementary pdf Supplementary Material Project Page DOI Project Page [BibTex]

OpenDR: An Approximate Differentiable Renderer

Loper, M. M., Black, M. J.

In Computer Vision – ECCV 2014, 8695, pages: 154-169, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

Inverse graphics attempts to take sensor data and infer 3D geometry, illumination, materials, and motions such that a graphics renderer could realistically reproduce the observed scene. Renderers, however, are designed to solve the forward process of image synthesis. To go in the other direction, we propose an approximate differentiable renderer (DR) that explicitly models the relationship between changes in model parameters and image observations. We describe a publicly available OpenDR framework that makes it easy to express a forward graphics model and then automatically obtain derivatives with respect to the model parameters and to optimize over them. Built on a new autodifferentiation package and OpenGL, OpenDR provides a local optimization method that can be incorporated into probabilistic programming frameworks. We demonstrate the power and simplicity of programming with OpenDR by using it to solve the problem of estimating human body shape from Kinect depth and RGB data.

pdf Code Chumpy Supplementary video of talk DOI Project Page [BibTex]

Loper, M. M., Black, M. J. OpenDR: An Approximate Differentiable Renderer In Computer Vision – ECCV 2014, 8695, pages: 154-169, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf Code Chumpy Supplementary video of talk DOI Project Page [BibTex]

Discovering Object Classes from Activities

Srikantha, A., Gall, J.

In European Conference on Computer Vision, 8694, pages: 415-430, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

In order to avoid an expensive manual labeling process or to learn object classes autonomously without human intervention, object discovery techniques have been proposed that extract visual similar objects from weakly labelled videos. However, the problem of discovering small or medium sized objects is largely unexplored. We observe that videos with activities involving human-object interactions can serve as weakly labelled data for such cases. Since neither object appearance nor motion is distinct enough to discover objects in these videos, we propose a framework that samples from a space of algorithms and their parameters to extract sequences of object proposals. Furthermore, we model similarity of objects based on appearance and functionality, which is derived from human and object motion. We show that functionality is an important cue for discovering objects from activities and demonstrate the generality of the model on three challenging RGB-D and RGB datasets.

pdf anno poster DOI Project Page [BibTex]

Srikantha, A., Gall, J. Discovering Object Classes from Activities In European Conference on Computer Vision, 8694, pages: 415-430, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf anno poster DOI Project Page [BibTex]

Probabilistic Progress Bars

Kiefel, M., Schuler, C., Hennig, P.

In Conference on Pattern Recognition (GCPR), 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, September 2014 (inproceedings)

Abstract

Predicting the time at which the integral over a stochastic process reaches a target level is a value of interest in many applications. Often, such computations have to be made at low cost, in real time. As an intuitive example that captures many features of this problem class, we choose progress bars, a ubiquitous element of computer user interfaces. These predictors are usually based on simple point estimators, with no error modelling. This leads to fluctuating behaviour confusing to the user. It also does not provide a distribution prediction (risk values), which are crucial for many other application areas. We construct and empirically evaluate a fast, constant cost algorithm using a Gauss-Markov process model which provides more information to the user.

website+code pdf DOI [BibTex]

Kiefel, M., Schuler, C., Hennig, P. Probabilistic Progress Bars In Conference on Pattern Recognition (GCPR), 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, September 2014 (inproceedings)

website+code pdf DOI [BibTex]

Optical Flow Estimation with Channel Constancy

Sevilla-Lara, L., Sun, D., Learned-Miller, E. G., Black, M. J.

In Computer Vision – ECCV 2014, 8689, pages: 423-438, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

Large motions remain a challenge for current optical flow algorithms. Traditionally, large motions are addressed using multi-resolution representations like Gaussian pyramids. To deal with large displacements, many pyramid levels are needed and, if an object is small, it may be invisible at the highest levels. To address this we decompose images using a channel representation (CR) and replace the standard brightness constancy assumption with a descriptor constancy assumption. CRs can be seen as an over-segmentation of the scene into layers based on some image feature. If the appearance of a foreground object differs from the background then its descriptor will be different and they will be represented in different layers.We create a pyramid by smoothing these layers, without mixing foreground and background or losing small objects. Our method estimates more accurate flow than the baseline on the MPI-Sintel benchmark, especially for fast motions and near motion boundaries.

pdf DOI [BibTex]

Sevilla-Lara, L., Sun, D., Learned-Miller, E. G., Black, M. J. Optical Flow Estimation with Channel Constancy In Computer Vision – ECCV 2014, 8689, pages: 423-438, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf DOI [BibTex]

Modeling Blurred Video with Layers

Wulff, J., Black, M. J.

In Computer Vision – ECCV 2014, 8694, pages: 236-252, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

Videos contain complex spatially-varying motion blur due to the combination of object motion, camera motion, and depth variation with finite shutter speeds. Existing methods to estimate optical flow, deblur the images, and segment the scene fail in such cases. In particular, boundaries between differently moving objects cause problems, because here the blurred images are a combination of the blurred appearances of multiple surfaces. We address this with a novel layered model of scenes in motion. From a motion-blurred video sequence, we jointly estimate the layer segmentation and each layer's appearance and motion. Since the blur is a function of the layer motion and segmentation, it is completely determined by our generative model. Given a video, we formulate the optimization problem as minimizing the pixel error between the blurred frames and images synthesized from the model, and solve it using gradient descent. We demonstrate our approach on synthetic and real sequences.

pdf Supplemental Video Data DOI Project Page Project Page [BibTex]

Wulff, J., Black, M. J. Modeling Blurred Video with Layers In Computer Vision – ECCV 2014, 8694, pages: 236-252, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf Supplemental Video Data DOI Project Page Project Page [BibTex]

Intrinsic Video

Kong, N., Gehler, P. V., Black, M. J.

In Computer Vision – ECCV 2014, 8690, pages: 360-375, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

Intrinsic images such as albedo and shading are valuable for later stages of visual processing. Previous methods for extracting albedo and shading use either single images or images together with depth data. Instead, we define intrinsic video estimation as the problem of extracting temporally coherent albedo and shading from video alone. Our approach exploits the assumption that albedo is constant over time while shading changes slowly. Optical flow aids in the accurate estimation of intrinsic video by providing temporal continuity as well as putative surface boundaries. Additionally, we find that the estimated albedo sequence can be used to improve optical flow accuracy in sequences with changing illumination. The approach makes only weak assumptions about the scene and we show that it substantially outperforms existing single-frame intrinsic image methods. We evaluate this quantitatively on synthetic sequences as well on challenging natural sequences with complex geometry, motion, and illumination.

pdf Supplementary Video DOI Project Page Project Page [BibTex]

Kong, N., Gehler, P. V., Black, M. J. Intrinsic Video In Computer Vision – ECCV 2014, 8690, pages: 360-375, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf Supplementary Video DOI Project Page Project Page [BibTex]

Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model

Bogo, F., Romero, J., Peserico, E., Black, M. J.

In Medical Image Computing and Computer-Assisted Intervention (MICCAI), 8673, pages: 593-600, Lecture Notes in Computer Science, (Editors: Golland, Polina and Hata, Nobuhiko and Barillot, Christian and Hornegger, Joachim and Howe, Robert), Spring International Publishing, September 2014 (inproceedings)

Abstract

Detection of new or rapidly evolving melanocytic lesions is crucial for early diagnosis and treatment of melanoma.We propose a fully automated pre-screening system for detecting new lesions or changes in existing ones, on the order of 2 - 3mm, over almost the entire body surface. Our solution is based on a multi-camera 3D stereo system. The system captures 3D textured scans of a subject at different times and then brings these scans into correspondence by aligning them with a learned, parametric, non-rigid 3D body model. This means that captured skin textures are in accurate alignment across scans, facilitating the detection of new or changing lesions. The integration of lesion segmentation with a deformable 3D body model is a key contribution that makes our approach robust to changes in illumination and subject pose.

pdf Poster DOI Project Page [BibTex]

Bogo, F., Romero, J., Peserico, E., Black, M. J. Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model In Medical Image Computing and Computer-Assisted Intervention (MICCAI), 8673, pages: 593-600, Lecture Notes in Computer Science, (Editors: Golland, Polina and Hata, Nobuhiko and Barillot, Christian and Hornegger, Joachim and Howe, Robert), Spring International Publishing, September 2014 (inproceedings)

pdf Poster DOI Project Page [BibTex]

Tracking using Multilevel Quantizations

Hong, Z., Wang, C., Mei, X., Prokhorov, D., Tao, D.

In Computer Vision – ECCV 2014, 8694, pages: 155-171, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

Abstract

Most object tracking methods only exploit a single quantization of an image space: pixels, superpixels, or bounding boxes, each of which has advantages and disadvantages. It is highly unlikely that a common optimal quantization level, suitable for tracking all objects in all environments, exists. We therefore propose a hierarchical appearance representation model for tracking, based on a graphical model that exploits shared information across multiple quantization levels. The tracker aims to find the most possible position of the target by jointly classifying the pixels and superpixels and obtaining the best configuration across all levels. The motion of the bounding box is taken into consideration, while Online Random Forests are used to provide pixel- and superpixel-level quantizations and progressively updated on-the-fly. By appropriately considering the multilevel quantizations, our tracker exhibits not only excellent performance in non-rigid object deformation handling, but also its robustness to occlusions. A quantitative evaluation is conducted on two benchmark datasets: a non-rigid object tracking dataset (11 sequences) and the CVPR2013 tracking benchmark (50 sequences). Experimental results show that our tracker overcomes various tracking challenges and is superior to a number of other popular tracking methods.

pdf DOI [BibTex]

Hong, Z., Wang, C., Mei, X., Prokhorov, D., Tao, D. Tracking using Multilevel Quantizations In Computer Vision – ECCV 2014, 8694, pages: 155-171, Lecture Notes in Computer Science, (Editors: D. Fleet and T. Pajdla and B. Schiele and T. Tuytelaars ), Springer International Publishing, September 2014 (inproceedings)

pdf DOI [BibTex]

The RoCKIn@Home User Story

Schneider, S., Hegger, F., Kraetzschmar, G., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Iocchi, L., Lima, P., Matteucci, M., Nardi, D., Awaad, I., Ahmad, A., Fontana, G., Hochgeschwender, N., Schiaffonati, V.

June 2014 (conference)

[BibTex]

Overview on the RoCKIn@Work Challenge

Dwiputra, R., Berghofer, J., Amigoni, F., Bischoff, R., Bonarini, A., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Ahmad, A., Awaad, I., Fontana, G., Hegger, F., Hochgeschwender, N., Schiaffonati, V., Schneider, S.

June 2014 (conference)

[BibTex]

Human Pose Estimation: New Benchmark and State of the Art Analysis

Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3686 - 3693, IEEE, June 2014 (inproceedings)

pdf DOI Project Page Project Page Project Page [BibTex]

Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B. Human Pose Estimation: New Benchmark and State of the Art Analysis In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3686 - 3693, IEEE, June 2014 (inproceedings)

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FAUST: Dataset and evaluation for 3D mesh registration

(Dataset Award, Eurographics Symposium on Geometry Processing (SGP), 2016)

Bogo, F., Romero, J., Loper, M., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3794 -3801, Columbus, Ohio, USA, June 2014 (inproceedings)

Abstract

New scanning technologies are increasing the importance of 3D mesh data and the need for algorithms that can reliably align it. Surface registration is important for building full 3D models from partial scans, creating statistical shape models, shape retrieval, and tracking. The problem is particularly challenging for non-rigid and articulated objects like human bodies. While the challenges of real-world data registration are not present in existing synthetic datasets, establishing ground-truth correspondences for real 3D scans is difficult. We address this with a novel mesh registration technique that combines 3D shape and appearance information to produce high-quality alignments. We define a new dataset called FAUST that contains 300 scans of 10 people in a wide range of poses together with an evaluation methodology. To achieve accurate registration, we paint the subjects with high-frequency textures and use an extensive validation process to ensure accurate ground truth. We find that current shape registration methods have trouble with this real-world data. The dataset and evaluation website are available for research purposes at http://faust.is.tue.mpg.de.

pdf Video Dataset Poster Talk DOI Project Page Project Page Project Page [BibTex]

Bogo, F., Romero, J., Loper, M., Black, M. J. FAUST: Dataset and evaluation for 3D mesh registration In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3794 -3801, Columbus, Ohio, USA, June 2014 (inproceedings)

pdf Video Dataset Poster Talk DOI Project Page Project Page Project Page [BibTex]

Model Transport: Towards Scalable Transfer Learning on Manifolds

Freifeld, O., Hauberg, S., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1378 -1385, Columbus, Ohio, USA, June 2014 (inproceedings)

Abstract

We consider the intersection of two research fields: transfer learning and statistics on manifolds. In particular, we consider, for manifold-valued data, transfer learning of tangent-space models such as Gaussians distributions, PCA, regression, or classifiers. Though one would hope to simply use ordinary Rn-transfer learning ideas, the manifold structure prevents it. We overcome this by basing our method on inner-product-preserving parallel transport, a well-known tool widely used in other problems of statistics on manifolds in computer vision. At first, this straightforward idea seems to suffer from an obvious shortcoming: Transporting large datasets is prohibitively expensive, hindering scalability. Fortunately, with our approach, we never transport data. Rather, we show how the statistical models themselves can be transported, and prove that for the tangent-space models above, the transport “commutes” with learning. Consequently, our compact framework, applicable to a large class of manifolds, is not restricted by the size of either the training or test sets. We demonstrate the approach by transferring PCA and logistic-regression models of real-world data involving 3D shapes and image descriptors.

pdf SupMat Video poster DOI Project Page [BibTex]

Freifeld, O., Hauberg, S., Black, M. J. Model Transport: Towards Scalable Transfer Learning on Manifolds In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1378 -1385, Columbus, Ohio, USA, June 2014 (inproceedings)

pdf SupMat Video poster DOI Project Page [BibTex]

Robot Arm Pose Estimation through Pixel-Wise Part Classification

Bohg, J., Romero, J., Herzog, A., Schaal, S.

In IEEE International Conference on Robotics and Automation (ICRA) 2014, pages: 3143-3150, June 2014 (inproceedings)

Abstract

We propose to frame the problem of marker-less robot arm pose estimation as a pixel-wise part classification problem. As input, we use a depth image in which each pixel is classified to be either from a particular robot part or the background. The classifier is a random decision forest trained on a large number of synthetically generated and labeled depth images. From all the training samples ending up at a leaf node, a set of offsets is learned that votes for relative joint positions. Pooling these votes over all foreground pixels and subsequent clustering gives us an estimate of the true joint positions. Due to the intrinsic parallelism of pixel-wise classification, this approach can run in super real-time and is more efficient than previous ICP-like methods. We quantitatively evaluate the accuracy of this approach on synthetic data. We also demonstrate that the method produces accurate joint estimates on real data despite being purely trained on synthetic data.

video code pdf DOI Project Page [BibTex]

Bohg, J., Romero, J., Herzog, A., Schaal, S. Robot Arm Pose Estimation through Pixel-Wise Part Classification In IEEE International Conference on Robotics and Automation (ICRA) 2014, pages: 3143-3150, June 2014 (inproceedings)

video code pdf DOI Project Page [BibTex]

Efficient Non-linear Markov Models for Human Motion

Lehrmann, A. M., Gehler, P. V., Nowozin, S.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1314-1321, IEEE, June 2014 (inproceedings)

Abstract

Dynamic Bayesian networks such as Hidden Markov Models (HMMs) are successfully used as probabilistic models for human motion. The use of hidden variables makes them expressive models, but inference is only approximate and requires procedures such as particle filters or Markov chain Monte Carlo methods. In this work we propose to instead use simple Markov models that only model observed quantities. We retain a highly expressive dynamic model by using interactions that are nonlinear and non-parametric. A presentation of our approach in terms of latent variables shows logarithmic growth for the computation of exact loglikelihoods in the number of latent states. We validate our model on human motion capture data and demonstrate state-of-the-art performance on action recognition and motion completion tasks.

Project page pdf DOI Project Page [BibTex]

Lehrmann, A. M., Gehler, P. V., Nowozin, S. Efficient Non-linear Markov Models for Human Motion In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1314-1321, IEEE, June 2014 (inproceedings)

Project page pdf DOI Project Page [BibTex]

Grassmann Averages for Scalable Robust PCA

Hauberg, S., Feragen, A., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3810 -3817, Columbus, Ohio, USA, June 2014 (inproceedings)

Abstract

As the collection of large datasets becomes increasingly automated, the occurrence of outliers will increase – "big data" implies "big outliers". While principal component analysis (PCA) is often used to reduce the size of data, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA do not scale beyond small-to-medium sized datasets. To address this, we introduce the Grassmann Average (GA), which expresses dimensionality reduction as an average of the subspaces spanned by the data. Because averages can be efficiently computed, we immediately gain scalability. GA is inherently more robust than PCA, but we show that they coincide for Gaussian data. We exploit that averages can be made robust to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. Robustness can be with respect to vectors (subspaces) or elements of vectors; we focus on the latter and use a trimmed average. The resulting Trimmed Grassmann Average (TGA) is particularly appropriate for computer vision because it is robust to pixel outliers. The algorithm has low computational complexity and minimal memory requirements, making it scalable to "big noisy data." We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie.

pdf code supplementary material tutorial video results video talk poster DOI Project Page [BibTex]

Hauberg, S., Feragen, A., Black, M. J. Grassmann Averages for Scalable Robust PCA In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3810 -3817, Columbus, Ohio, USA, June 2014 (inproceedings)

pdf code supplementary material tutorial video results video talk poster DOI Project Page [BibTex]

Posebits for Monocular Human Pose Estimation

Pons-Moll, G., Fleet, D. J., Rosenhahn, B.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2345-2352, Columbus, Ohio, USA, June 2014 (inproceedings)

Abstract

We advocate the inference of qualitative information about 3D human pose, called posebits, from images. Posebits represent boolean geometric relationships between body parts (e.g., left-leg in front of right-leg or hands close to each other). The advantages of posebits as a mid-level representation are 1) for many tasks of interest, such qualitative pose information may be sufficient (e.g. , semantic image retrieval), 2) it is relatively easy to annotate large image corpora with posebits, as it simply requires answers to yes/no questions; and 3) they help resolve challenging pose ambiguities and therefore facilitate the difficult talk of image-based 3D pose estimation. We introduce posebits, a posebit database, a method for selecting useful posebits for pose estimation and a structural SVM model for posebit inference. Experiments show the use of posebits for semantic image retrieval and for improving 3D pose estimation.

pdf Project Page Project Page [BibTex]

Pons-Moll, G., Fleet, D. J., Rosenhahn, B. Posebits for Monocular Human Pose Estimation In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2345-2352, Columbus, Ohio, USA, June 2014 (inproceedings)

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Simultaneous Underwater Visibility Assessment, Enhancement and Improved Stereo

Roser, M., Dunbabin, M., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 3840 - 3847 , Hong Kong, China, June 2014 (conference)

Abstract

Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows real-time implementation onboard an Autonomous Underwater Vehicles for improved navigation and obstacle avoidance performance.

pdf DOI [BibTex]

Roser, M., Dunbabin, M., Geiger, A. Simultaneous Underwater Visibility Assessment, Enhancement and Improved Stereo IEEE International Conference on Robotics and Automation, pages: 3840 - 3847 , Hong Kong, China, June 2014 (conference)

pdf DOI [BibTex]

Preserving Modes and Messages via Diverse Particle Selection

Pacheco, J., Zuffi, S., Black, M. J., Sudderth, E.

In Proceedings of the 31st International Conference on Machine Learning (ICML-14), 32(1):1152-1160, J. Machine Learning Research Workshop and Conf. and Proc., Beijing, China, June 2014 (inproceedings)

Abstract

In applications of graphical models arising in domains such as computer vision and signal processing, we often seek the most likely configurations of high-dimensional, continuous variables. We develop a particle-based max-product algorithm which maintains a diverse set of posterior mode hypotheses, and is robust to initialization. At each iteration, the set of hypotheses at each node is augmented via stochastic proposals, and then reduced via an efficient selection algorithm. The integer program underlying our optimization-based particle selection minimizes errors in subsequent max-product message updates. This objective automatically encourages diversity in the maintained hypotheses, without requiring tuning of application-specific distances among hypotheses. By avoiding the stochastic resampling steps underlying particle sum-product algorithms, we also avoid common degeneracies where particles collapse onto a single hypothesis. Our approach significantly outperforms previous particle-based algorithms in experiments focusing on the estimation of human pose from single images.

pdf SupMat link (url) Project Page Project Page [BibTex]

Pacheco, J., Zuffi, S., Black, M. J., Sudderth, E. Preserving Modes and Messages via Diverse Particle Selection In Proceedings of the 31st International Conference on Machine Learning (ICML-14), 32(1):1152-1160, J. Machine Learning Research Workshop and Conf. and Proc., Beijing, China, June 2014 (inproceedings)

pdf SupMat link (url) Project Page Project Page [BibTex]

Calibrating and Centering Quasi-Central Catadioptric Cameras

Schoenbein, M., Strauss, T., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 4443 - 4450, Hong Kong, China, June 2014 (conference)

Abstract

Non-central catadioptric models are able to cope with irregular camera setups and inaccuracies in the manufacturing process but are computationally demanding and thus not suitable for robotic applications. On the other hand, calibrating a quasi-central (almost central) system with a central model introduces errors due to a wrong relationship between the viewing ray orientations and the pixels on the image sensor. In this paper, we propose a central approximation to quasi-central catadioptric camera systems that is both accurate and efficient. We observe that the distance to points in 3D is typically large compared to deviations from the single viewpoint. Thus, we first calibrate the system using a state-of-the-art non-central camera model. Next, we show that by remapping the observations we are able to match the orientation of the viewing rays of a much simpler single viewpoint model with the true ray orientations. While our approximation is general and applicable to all quasi-central camera systems, we focus on one of the most common cases in practice: hypercatadioptric cameras. We compare our model to a variety of baselines in synthetic and real localization and motion estimation experiments. We show that by using the proposed model we are able to achieve near non-central accuracy while obtaining speed-ups of more than three orders of magnitude compared to state-of-the-art non-central models.

pdf DOI [BibTex]

Schoenbein, M., Strauss, T., Geiger, A. Calibrating and Centering Quasi-Central Catadioptric Cameras IEEE International Conference on Robotics and Automation, pages: 4443 - 4450, Hong Kong, China, June 2014 (conference)

pdf DOI [BibTex]

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

Hennig, P., Hauberg, S.

In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, April 2014 (inproceedings)

Abstract

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian manifolds, where non-analytic ordinary differential equations are involved in virtually all computations. The probabilistic formulation permits marginalising the uncertainty of the numerical solution such that statistics are less sensitive to inaccuracies. This leads to new Riemannian algorithms for mean value computations and principal geodesic analysis. Marginalisation also means results can be less precise than point estimates, enabling a noticeable speed-up over the state of the art. Our approach is an argument for a wider point that uncertainty caused by numerical calculations should be tracked throughout the pipeline of machine learning algorithms.

pdf Youtube Supplements Project page link (url) [BibTex]

Hennig, P., Hauberg, S. Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, April 2014 (inproceedings)

pdf Youtube Supplements Project page link (url) [BibTex]

Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

Pepik, B., Stark, M., Gehler, P., Schiele, B.

International Conference on Learning Representations, April 2014 (conference)

Abstract

While the majority of today's object class models provide only 2D bounding boxes, far richer output hypotheses are desirable including viewpoint, fine-grained category, and 3D geometry estimate. However, models trained to provide richer output require larger amounts of training data, preferably well covering the relevant aspects such as viewpoint and fine-grained categories. In this paper, we address this issue from the perspective of transfer learning, and design an object class model that explicitly leverages correlations between visual features. Specifically, our model represents prior distributions over permissible multi-view detectors in a parametric way -- the priors are learned once from training data of a source object class, and can later be used to facilitate the learning of a detector for a target class. As we show in our experiments, this transfer is not only beneficial for detectors based on basic-level category representations, but also enables the robust learning of detectors that represent classes at finer levels of granularity, where training data is typically even scarcer and more unbalanced. As a result, we report largely improved performance in simultaneous 2D object localization and viewpoint estimation on a recent dataset of challenging street scenes.

reviews pdf Project Page [BibTex]

Pepik, B., Stark, M., Gehler, P., Schiele, B. Multi-View Priors for Learning Detectors from Sparse Viewpoint Data International Conference on Learning Representations, April 2014 (conference)

reviews pdf Project Page [BibTex]

NRSfM using Local Rigidity

Rehan, A., Zaheer, A., Akhter, I., Saeed, A., Mahmood, B., Usmani, M., Khan, S.

In Proceedings Winter Conference on Applications of Computer Vision, pages: 69-74, open access, IEEE , Steamboat Springs, CO, USA, March 2014 (inproceedings)

Abstract

Factorization methods for computation of nonrigid structure have limited practicality, and work well only when there is large enough camera motion between frames, with long sequences and limited or no occlusions. We show that typical nonrigid structure can often be approximated well as locally rigid sub-structures in time and space. Specifically, we assume that: 1) the structure can be approximated as rigid in a short local time window and 2) some point pairs stay relatively rigid in space, maintaining a fixed distance between them during the sequence. We first use the triangulation constraints in rigid SFM over a sliding time window to get an initial estimate of the nonrigid 3D structure. We then automatically identify relatively rigid point pairs in this structure, and use their length-constancy simultaneously with triangulation constraints to refine the structure estimate. Unlike factorization methods, the structure is estimated independent of the camera motion computation, adding to the simplicity and stability of the approach. Further, local factorization inherently handles significant natural occlusions gracefully, performing much better than the state-of-the art. We show more stable and accurate results as compared to the state-of-the art on even short sequences starting from 15 frames only, containing camera rotations as small as 2 degree and up to 50% missing data.

link (url) [BibTex]

Rehan, A., Zaheer, A., Akhter, I., Saeed, A., Mahmood, B., Usmani, M., Khan, S. NRSfM using Local Rigidity In Proceedings Winter Conference on Applications of Computer Vision, pages: 69-74, open access, IEEE , Steamboat Springs, CO, USA, March 2014 (inproceedings)

link (url) [BibTex]

Model-based Anthropometry: Predicting Measurements from 3D Human Scans in Multiple Poses

Tsoli, A., Loper, M., Black, M. J.

In Proceedings Winter Conference on Applications of Computer Vision, pages: 83-90, IEEE , March 2014 (inproceedings)

Abstract

Extracting anthropometric or tailoring measurements from 3D human body scans is important for applications such as virtual try-on, custom clothing, and online sizing. Existing commercial solutions identify anatomical landmarks on high-resolution 3D scans and then compute distances or circumferences on the scan. Landmark detection is sensitive to acquisition noise (e.g. holes) and these methods require subjects to adopt a specific pose. In contrast, we propose a solution we call model-based anthropometry. We fit a deformable 3D body model to scan data in one or more poses; this model-based fitting is robust to scan noise. This brings the scan into registration with a database of registered body scans. Then, we extract features from the registered model (rather than from the scan); these include, limb lengths, circumferences, and statistical features of global shape. Finally, we learn a mapping from these features to measurements using regularized linear regression. We perform an extensive evaluation using the CAESAR dataset and demonstrate that the accuracy of our method outperforms state-of-the-art methods.

pdf DOI Project Page Project Page [BibTex]

Tsoli, A., Loper, M., Black, M. J. Model-based Anthropometry: Predicting Measurements from 3D Human Scans in Multiple Poses In Proceedings Winter Conference on Applications of Computer Vision, pages: 83-90, IEEE , March 2014 (inproceedings)

pdf DOI Project Page Project Page [BibTex]

Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

Restrepo, M. I., Ulusoy, A. O., Mundy, J. L.

In ISPRS Journal of Photogrammetry and Remote Sensing, 98(0):1-18, 2014 (inproceedings)

Abstract

Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the {PVM} to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of {PVMs} to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.

Publisher site link (url) DOI [BibTex]

Restrepo, M. I., Ulusoy, A. O., Mundy, J. L. Evaluation of feature-based 3-d registration of probabilistic volumetric scenes In ISPRS Journal of Photogrammetry and Remote Sensing, 98(0):1-18, 2014 (inproceedings)

Publisher site link (url) DOI [BibTex]

Left Ventricle Segmentation by Dynamic Shape Constrained Random Walk

X. Yang, Y. Su, M. Wan, S. Y. Yeo, C. Lim, S. T. Wong, L. Zhong, R. S. Tan

In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014 (inproceedings)

Abstract

Accurate and robust extraction of the left ventricle (LV) cavity is a key step for quantitative analysis of cardiac functions. In this study, we propose an improved LV cavity segmentation method that incorporates a dynamic shape constraint into the weighting function of the random walks algorithm. The method involves an iterative process that updates an intermediate result to the desired solution. The shape constraint restricts the solution space of the segmentation result, such that the robustness of the algorithm is increased to handle misleading information that emanates from noise, weak boundaries, and clutter. Our experiments on real cardiac magnetic resonance images demonstrate that the proposed method obtains better segmentation performance than standard method.

[BibTex]

X. Yang, Y. Su, M. Wan, S. Y. Yeo, C. Lim, S. T. Wong, L. Zhong, R. S. Tan Left Ventricle Segmentation by Dynamic Shape Constrained Random Walk In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014 (inproceedings)

[BibTex]

2011

Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling

Pons-Moll, G., Baak, A., Gall, J., Leal-Taixe, L., Mueller, M., Seidel, H., Rosenhahn, B.

In IEEE International Conference on Computer Vision (ICCV), pages: 1243-1250, November 2011 (inproceedings)

project page pdf supplemental [BibTex]

2011

Pons-Moll, G., Baak, A., Gall, J., Leal-Taixe, L., Mueller, M., Seidel, H., Rosenhahn, B. Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling In IEEE International Conference on Computer Vision (ICCV), pages: 1243-1250, November 2011 (inproceedings)

project page pdf supplemental [BibTex]

Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M.

In Int. Conf. on Computer Vision (ICCV), pages: 1951-1958, IEEE, Barcelona, November 2011 (inproceedings)

Abstract

The 3D shape of the human body is useful for applications in fitness, games and apparel. Accurate body scanners, however, are expensive, limiting the availability of 3D body models. We present a method for human shape reconstruction from noisy monocular image and range data using a single inexpensive commodity sensor. The approach combines low-resolution image silhouettes with coarse range data to estimate a parametric model of the body. Accurate 3D shape estimates are obtained by combining multiple monocular views of a person moving in front of the sensor. To cope with varying body pose, we use a SCAPE body model which factors 3D body shape and pose variations. This enables the estimation of a single consistent shape while allowing pose to vary. Additionally, we describe a novel method to minimize the distance between the projected 3D body contour and the image silhouette that uses analytic derivatives of the objective function. We propose a simple method to estimate standard body measurements from the recovered SCAPE model and show that the accuracy of our method is competitive with commercial body scanning systems costing orders of magnitude more.

pdf YouTube poster Project Page Project Page [BibTex]

Weiss, A., Hirshberg, D., Black, M. Home 3D body scans from noisy image and range data In Int. Conf. on Computer Vision (ICCV), pages: 1951-1958, IEEE, Barcelona, November 2011 (inproceedings)

pdf YouTube poster Project Page Project Page [BibTex]

Means in spaces of tree-like shapes

Aasa Feragen, Soren Hauberg, Mads Nielsen, Francois Lauze

In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 736 -746, IEEE, november 2011 (inproceedings)

Publishers site PDF Suppl. material [BibTex]

Aasa Feragen, Soren Hauberg, Mads Nielsen, Francois Lauze Means in spaces of tree-like shapes In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 736 -746, IEEE, november 2011 (inproceedings)

Publishers site PDF Suppl. material [BibTex]

Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker

Leal-Taixé, L., Rosenhahn, G. P. A. B.

In IEEE International Conference on Computer Vision Workshops (IICCVW), November 2011 (inproceedings)

project page pdf [BibTex]

Leal-Taixé, L., Rosenhahn, G. P. A. B. Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker In IEEE International Conference on Computer Vision Workshops (IICCVW), November 2011 (inproceedings)

project page pdf [BibTex]

Evaluating the Automated Alignment of 3D Human Body Scans

Hirshberg, D. A., Loper, M., Rachlin, E., Tsoli, A., Weiss, A., Corner, B., Black, M. J.

In 2nd International Conference on 3D Body Scanning Technologies, pages: 76-86, (Editors: D’Apuzzo, Nicola), Hometrica Consulting, Lugano, Switzerland, October 2011 (inproceedings)

Abstract

The statistical analysis of large corpora of human body scans requires that these scans be in alignment, either for a small set of key landmarks or densely for all the vertices in the scan. Existing techniques tend to rely on hand-placed landmarks or algorithms that extract landmarks from scans. The former is time consuming and subjective while the latter is error prone. Here we show that a model-based approach can align meshes automatically, producing alignment accuracy similar to that of previous methods that rely on many landmarks. Specifically, we align a low-resolution, artist-created template body mesh to many high-resolution laser scans. Our alignment procedure employs a robust iterative closest point method with a regularization that promotes smooth and locally rigid deformation of the template mesh. We evaluate our approach on 50 female body models from the CAESAR dataset that vary significantly in body shape. To make the method fully automatic, we define simple feature detectors for the head and ankles, which provide initial landmark locations. We find that, if body poses are fairly similar, as in CAESAR, the fully automated method provides dense alignments that enable statistical analysis and anthropometric measurement.

pdf slides DOI Project Page [BibTex]

Hirshberg, D. A., Loper, M., Rachlin, E., Tsoli, A., Weiss, A., Corner, B., Black, M. J. Evaluating the Automated Alignment of 3D Human Body Scans In 2nd International Conference on 3D Body Scanning Technologies, pages: 76-86, (Editors: D’Apuzzo, Nicola), Hometrica Consulting, Lugano, Switzerland, October 2011 (inproceedings)

pdf slides DOI Project Page [BibTex]

Branch&Rank: Non-Linear Object Detection

(Best Impact Paper Prize)

Lehmann, A., Gehler, P., VanGool, L.

In Proceedings of the British Machine Vision Conference (BMVC), pages: 8.1-8.11, (Editors: Jesse Hoey and Stephen McKenna and Emanuele Trucco), BMVA Press, September 2011, http://dx.doi.org/10.5244/C.25.8 (inproceedings)

video of talk pdf slides supplementary [BibTex]

Lehmann, A., Gehler, P., VanGool, L. Branch&Rank: Non-Linear Object Detection In Proceedings of the British Machine Vision Conference (BMVC), pages: 8.1-8.11, (Editors: Jesse Hoey and Stephen McKenna and Emanuele Trucco), BMVA Press, September 2011, http://dx.doi.org/10.5244/C.25.8 (inproceedings)

video of talk pdf slides supplementary [BibTex]

Efficient and Robust Shape Matching for Model Based Human Motion Capture

Pons-Moll, G., Leal-Taixé, L., Truong, T., Rosenhahn, B.

In German Conference on Pattern Recognition (GCPR), pages: 416-425, September 2011 (inproceedings)

project page pdf [BibTex]

Pons-Moll, G., Leal-Taixé, L., Truong, T., Rosenhahn, B. Efficient and Robust Shape Matching for Model Based Human Motion Capture In German Conference on Pattern Recognition (GCPR), pages: 416-425, September 2011 (inproceedings)

project page pdf [BibTex]

BrainGate pilot clinical trials: Progress in translating neural engineering principles to clinical testing

33rd Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, August 2011 (conference)

[BibTex]

Hochberg, L., Simeral, J., Black, M., Bacher, D., Barefoot, L., Berhanu, E., Borton, D., Cash, S., Feldman, J., Gallivan, E., Homer, M., Jarosiewicz, B., King, B., Liu, J., Malik, W., Masse, N., Perge, J., Rosler, D., Schmansky, N., Travers, B., Truccolo, W., Nurmikko, A., Donoghue, J. BrainGate pilot clinical trials: Progress in translating neural engineering principles to clinical testing 33rd Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, August 2011 (conference)

[BibTex]

Learning Output Kernels with Block Coordinate Descent

Dinuzzo, F., Ong, C. S., Gehler, P., Pillonetto, G.

In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pages: 49-56, ICML ’11, (Editors: Getoor, Lise and Scheffer, Tobias), ACM, New York, NY, USA, June 2011 (inproceedings)

data+code pdf [BibTex]

Dinuzzo, F., Ong, C. S., Gehler, P., Pillonetto, G. Learning Output Kernels with Block Coordinate Descent In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pages: 49-56, ICML ’11, (Editors: Getoor, Lise and Scheffer, Tobias), ACM, New York, NY, USA, June 2011 (inproceedings)

data+code pdf [BibTex]

Role of expertise and contralateral symmetry in the diagnosis of pneumoconiosis: an experimental study

Jampani, V., Vaidya, V., Sivaswamy, J., Tourani, K. L.

In Proc. SPIE 7966, Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, 2011, Florida, March 2011 (inproceedings)

Abstract

Pneumoconiosis, a lung disease caused by the inhalation of dust, is mainly diagnosed using chest radiographs. The effects of using contralateral symmetric (CS) information present in chest radiographs in the diagnosis of pneumoconiosis are studied using an eye tracking experimental study. The role of expertise and the influence of CS information on the performance of readers with different expertise level are also of interest. Experimental subjects ranging from novices & medical students to staff radiologists were presented with 17 double and 16 single lung images, and were asked to give profusion ratings for each lung zone. Eye movements and the time for their diagnosis were also recorded. Kruskal-Wallis test (χ2(6) = 13.38, p = .038), showed that the observer error (average sum of absolute differences) in double lung images differed significantly across the different expertise categories when considering all the participants. Wilcoxon-signed rank test indicated that the observer error was significantly higher for single-lung images (Z = 3.13, p < .001) than for the double-lung images for all the participants. Mann-Whitney test (U = 28, p = .038) showed that the differential error between single and double lung images is significantly higher in doctors [staff & residents] than in non-doctors [others]. Thus, Expertise & CS information plays a significant role in the diagnosis of pneumoconiosis. CS information helps in diagnosing pneumoconiosis by reducing the general tendency of giving less profusion ratings. Training and experience appear to play important roles in learning to use the CS information present in the chest radiographs.

url link (url) [BibTex]

Jampani, V., Vaidya, V., Sivaswamy, J., Tourani, K. L. Role of expertise and contralateral symmetry in the diagnosis of pneumoconiosis: an experimental study In Proc. SPIE 7966, Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, 2011, Florida, March 2011 (inproceedings)

url link (url) [BibTex]

Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance

Gehler, P., Rother, C., Kiefel, M., Zhang, L., Schölkopf, B.

In Advances in Neural Information Processing Systems 24, pages: 765-773, (Editors: Shawe-Taylor, John and Zemel, Richard S. and Bartlett, Peter L. and Pereira, Fernando C. N. and Weinberger, Kilian Q.), Curran Associates, Inc., Red Hook, NY, USA, 2011 (inproceedings)

Abstract

We address the challenging task of decoupling material properties from lighting properties given a single image. In the last two decades virtually all works have concentrated on exploiting edge information to address this problem. We take a different route by introducing a new prior on reflectance, that models reflectance values as being drawn from a sparse set of basis colors. This results in a Random Field model with global, latent variables (basis colors) and pixel-accurate output reflectance values. We show that without edge information high-quality results can be achieved, that are on par with methods exploiting this source of information. Finally, we are able to improve on state-of-the-art results by integrating edge information into our model. We believe that our new approach is an excellent starting point for future developments in this field.

website + code pdf poster Project Page Project Page [BibTex]

Gehler, P., Rother, C., Kiefel, M., Zhang, L., Schölkopf, B. Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance In Advances in Neural Information Processing Systems 24, pages: 765-773, (Editors: Shawe-Taylor, John and Zemel, Richard S. and Bartlett, Peter L. and Pereira, Fernando C. N. and Weinberger, Kilian Q.), Curran Associates, Inc., Red Hook, NY, USA, 2011 (inproceedings)

website + code pdf poster Project Page Project Page [BibTex]

OpenBioSafetyLab: A virtual world based biosafety training application for medical students

Nakasone, A., Tang, S., Shigematsu, M., Heinecke, B., Fujimoto, S., Prendinger, H.

In International Conference on Information Technology: New Generations (ITNG), IEEE CPS, 2011 (inproceedings)

PDF [BibTex]

Nakasone, A., Tang, S., Shigematsu, M., Heinecke, B., Fujimoto, S., Prendinger, H. OpenBioSafetyLab: A virtual world based biosafety training application for medical students In International Conference on Information Technology: New Generations (ITNG), IEEE CPS, 2011 (inproceedings)

PDF [BibTex]

Combining wireless neural recording and video capture for the analysis of natural gait

Foster, J., Freifeld, O., Nuyujukian, P., Ryu, S., Black, M. J., Shenoy, K.

In Proc. 5th Int. IEEE EMBS Conf. on Neural Engineering, pages: 613-616, IEEE, 2011 (inproceedings)

pdf Project Page [BibTex]

Foster, J., Freifeld, O., Nuyujukian, P., Ryu, S., Black, M. J., Shenoy, K. Combining wireless neural recording and video capture for the analysis of natural gait In Proc. 5th Int. IEEE EMBS Conf. on Neural Engineering, pages: 613-616, IEEE, 2011 (inproceedings)

pdf Project Page [BibTex]

Tagged Cardiac MR Image Segmentation Using Boundary & Regional-Support and Graph-based Deformable Priors

Xiang, B., Wang, C., Deux, J., Rahmouni, A., Paragios, N.

In IEEE International Symposium on Biomedical Imaging (ISBI), 2011 (inproceedings)

pdf [BibTex]

Xiang, B., Wang, C., Deux, J., Rahmouni, A., Paragios, N. Tagged Cardiac MR Image Segmentation Using Boundary & Regional-Support and Graph-based Deformable Priors In IEEE International Symposium on Biomedical Imaging (ISBI), 2011 (inproceedings)

pdf [BibTex]

Multiview Structure from Motion in Trajectory Space

Zaheer, A., Akhter, I., Mohammad, H. B., Marzban, S., Khan, S.

In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 2447-2453, 2011 (inproceedings)

Abstract

Most nonrigid objects exhibit temporal regularities in their deformations. Recently it was proposed that these regularities can be parameterized by assuming that the non- rigid structure lies in a small dimensional trajectory space. In this paper, we propose a factorization approach for 3D reconstruction from multiple static cameras under the com- pact trajectory subspace representation. Proposed factor- ization is analogous to rank-3 factorization of rigid struc- ture from motion problem, in transformed space. The benefit of our approach is that the 3D trajectory basis can be directly learned from the image observations. This also allows us to impute missing observations and denoise tracking errors without explicit estimation of the 3D structure. In contrast to standard triangulation based methods which require points to be visible in at least two cameras, our ap- proach can reconstruct points, which remain occluded even in all the cameras for quite a long time. This makes our solution especially suitable for occlusion handling in motion capture systems. We demonstrate robustness of our method on challenging real and synthetic scenarios.

pdf project page [BibTex]

Zaheer, A., Akhter, I., Mohammad, H. B., Marzban, S., Khan, S. Multiview Structure from Motion in Trajectory Space In Computer Vision (ICCV), 2011 IEEE International Conference on, pages: 2447-2453, 2011 (inproceedings)

pdf project page [BibTex]

Unscented Kalman Filtering for Articulated Human Tracking

Anders Boesen Lindbo Larsen, Soren Hauberg, Kim S. Pedersen

In Image Analysis, 6688, pages: 228-237, Lecture Notes in Computer Science, (Editors: Heyden, Anders and Kahl, Fredrik), Springer Berlin Heidelberg, 2011 (inproceedings)

Publishers site PDF [BibTex]

Anders Boesen Lindbo Larsen, Soren Hauberg, Kim S. Pedersen Unscented Kalman Filtering for Articulated Human Tracking In Image Analysis, 6688, pages: 228-237, Lecture Notes in Computer Science, (Editors: Heyden, Anders and Kahl, Fredrik), Springer Berlin Heidelberg, 2011 (inproceedings)

Publishers site PDF [BibTex]

Adaptation for perception of the human body: Investigations of transfer across viewpoint and pose

Sekunova, A., Black, M. J., Parkinson, L., Barton, J. S.

Vision Sciences Society, 2011 (conference)

[BibTex]

Sekunova, A., Black, M. J., Parkinson, L., Barton, J. S. Adaptation for perception of the human body: Investigations of transfer across viewpoint and pose Vision Sciences Society, 2011 (conference)

[BibTex]

Level Set Segmentation with Robust Image Gradient Energy and Statistical Shape Prior

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

In IEEE International Conference on Image Processing, pages: 3397 - 3400, 2011 (inproceedings)

Abstract

We propose a new level set segmentation method with statistical shape prior using a variational approach. The image energy is derived from a robust image gradient feature. This gives the active contour a global representation of the geometric configuration, making it more robust to image noise, weak edges and initial configurations. Statistical shape information is incorporated using nonparametric shape density distribution, which allows the model to handle relatively large shape variations. Comparative examples using both synthetic and real images show the robustness and efficiency of the proposed method.

link (url) [BibTex]

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu Level Set Segmentation with Robust Image Gradient Energy and Statistical Shape Prior In IEEE International Conference on Image Processing, pages: 3397 - 3400, 2011 (inproceedings)

link (url) [BibTex]

Variational Level Set Segmentation Using Shape Prior

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

In International Conference on Mathematical and Computational Biomedical Engineering, 2011 (inproceedings)

[BibTex]

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu Variational Level Set Segmentation Using Shape Prior In International Conference on Mathematical and Computational Biomedical Engineering, 2011 (inproceedings)

[BibTex]

HMDB: A Large Video Database for Human Motion Recognition

Kuhne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.

In IEEE International Conference on Computer Vision (ICCV), 2011 (inproceedings)

code, webpage, dataset pdf [BibTex]

Kuhne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T. HMDB: A Large Video Database for Human Motion Recognition In IEEE International Conference on Computer Vision (ICCV), 2011 (inproceedings)

code, webpage, dataset pdf [BibTex]

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