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2012


Thumb xl bilinear
Bilinear Spatiotemporal Basis Models

Akhter, I., Simon, T., Khan, S., Matthews, I., Sheikh, Y.

ACM Transactions on Graphics (TOG), 31(2):17, ACM, April 2012 (article)

Abstract
A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer graphics as a collection of moving spatial landmarks. Spatiotemporal data is inherent in a number of graphics applications including animation, simulation, and object and camera tracking. The principal modes of variation in the spatial geometry of objects are typically modeled using dimensionality reduction techniques, while concurrently, trajectory representations like splines and autoregressive models are widely used to exploit the temporal regularity of deformation. In this article, we present the bilinear spatiotemporal basis as a model that simultaneously exploits spatial and temporal regularity while maintaining the ability to generalize well to new sequences. This factorization allows the use of analytical, predefined functions to represent temporal variation (e.g., B-Splines or the Discrete Cosine Transform) resulting in efficient model representation and estimation. The model can be interpreted as representing the data as a linear combination of spatiotemporal sequences consisting of shape modes oscillating over time at key frequencies. We apply the bilinear model to natural spatiotemporal phenomena, including face, body, and cloth motion data, and compare it in terms of compaction, generalization ability, predictive precision, and efficiency to existing models. We demonstrate the application of the model to a number of graphics tasks including labeling, gap-filling, denoising, and motion touch-up.

pdf project page link (url) [BibTex]

2012

pdf project page link (url) [BibTex]


Thumb xl teaser dagstuhl lau
Exploiting pedestrian interaction via global optimization and social behaviors

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

In Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis, Springer, April 2012 (incollection)

pdf [BibTex]

pdf [BibTex]


Thumb xl humim2012
HUMIM Software for Articulated Tracking

Soren Hauberg, Kim S. Pedersen

(01/2012), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

Code PDF [BibTex]

Code PDF [BibTex]


Thumb xl tr feragen2012
A geometric framework for statistics on trees

Aasa Feragen, Mads Nielsen, Soren Hauberg, Pechin Lo, Marleen de Bruijne, Francois Lauze

(11/02), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

PDF [BibTex]

PDF [BibTex]


Thumb xl rotationpose
Data-driven Manifolds for Outdoor Motion Capture

Pons-Moll, G., Leal-Taix’e, L., Gall, J., Rosenhahn, B.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 305-328, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

video publisher's site pdf Project Page [BibTex]

video publisher's site pdf Project Page [BibTex]


Thumb xl 3dimpvt2012
High Resolution Surface Reconstruction from Multi-view Aerial Imagery

Calakli, F., Ulusoy, A. O., Restrepo, M. I., Taubin, G., Mundy, J. L.

In 3D Imaging Modeling Processing Visualization Transmission (3DIMPVT), pages: 25-32, IEEE, 2012 (inproceedings)

Abstract
This paper presents a novel framework for surface reconstruction from multi-view aerial imagery of large scale urban scenes, which combines probabilistic volumetric modeling with smooth signed distance surface estimation, to produce very detailed and accurate surfaces. Using a continuous probabilistic volumetric model which allows for explicit representation of ambiguities caused by moving objects, reflective surfaces, areas of constant appearance, and self-occlusions, the algorithm learns the geometry and appearance of a scene from a calibrated image sequence. An online implementation of Bayesian learning precess in GPUs significantly reduces the time required to process a large number of images. The probabilistic volumetric model of occupancy is subsequently used to estimate a smooth approximation of the signed distance function to the surface. This step, which reduces to the solution of a sparse linear system, is very efficient and scalable to large data sets. The proposed algorithm is shown to produce high quality surfaces in challenging aerial scenes where previous methods make large errors in surface localization. The general applicability of the algorithm beyond aerial imagery is confirmed against the Middlebury benchmark.

Video pdf link (url) DOI [BibTex]

Video pdf link (url) DOI [BibTex]


Thumb xl tang2012bmvc
Detection and Tracking of Occluded People

(Best Paper Award)

Tang, S., Andriluka, M., Schiele, B.

In British Machine Vision Conference (BMVC), 2012, BMVC Best Paper Award (inproceedings)

PDF [BibTex]

PDF [BibTex]


Thumb xl segmentation isbi12
3D Cardiac Segmentation with Pose-Invariant Higher-Order MRFs

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

In IEEE International Symposium on Biomedical Imaging (ISBI), 2012 (inproceedings)

[BibTex]

[BibTex]


Thumb xl facialfeature
Real-time Facial Feature Detection using Conditional Regression Forests

Dantone, M., Gall, J., Fanelli, G., van Gool, L.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 2578-2585, IEEE, Providence, RI, USA, 2012 (inproceedings)

code pdf Project Page [BibTex]

code pdf Project Page [BibTex]


Thumb xl lht
Latent Hough Transform for Object Detection

Razavi, N., Gall, J., Kohli, P., van Gool, L.

In European Conference on Computer Vision (ECCV), 7574, pages: 312-325, LNCS, Springer, 2012 (inproceedings)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


Thumb xl destflow
Destination Flow for Crowd Simulation

Pellegrini, S., Gall, J., Sigal, L., van Gool, L.

In Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, 7585, pages: 162-171, LNCS, Springer, 2012 (inproceedings)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


Thumb xl thumb latent space2
A metric for comparing the anthropomorphic motion capability of artificial hands

Feix, T., Romero, J., Ek, C. H., Schmiedmayer, H., Kragic, D.

IEEE RAS Transactions on Robotics, TRO, pages: 974-980, 2012 (article)

Publisher site Human Grasping Database Project [BibTex]

Publisher site Human Grasping Database Project [BibTex]


Thumb xl soumyanips
From Deformations to Parts: Motion-based Segmentation of 3D Objects

Ghosh, S., Sudderth, E., Loper, M., Black, M.

In Advances in Neural Information Processing Systems 25 (NIPS), pages: 2006-2014, (Editors: P. Bartlett and F.C.N. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberger), MIT Press, 2012 (inproceedings)

Abstract
We develop a method for discovering the parts of an articulated object from aligned meshes of the object in various three-dimensional poses. We adapt the distance dependent Chinese restaurant process (ddCRP) to allow nonparametric discovery of a potentially unbounded number of parts, while simultaneously guaranteeing a spatially connected segmentation. To allow analysis of datasets in which object instances have varying 3D shapes, we model part variability across poses via affine transformations. By placing a matrix normal-inverse-Wishart prior on these affine transformations, we develop a ddCRP Gibbs sampler which tractably marginalizes over transformation uncertainty. Analyzing a dataset of humans captured in dozens of poses, we infer parts which provide quantitatively better deformation predictions than conventional clustering methods.

pdf supplemental code poster link (url) Project Page [BibTex]

pdf supplemental code poster link (url) Project Page [BibTex]


Thumb xl rat4
The Ankyrin 3 (ANK3) Bipolar Disorder Gene Regulates Psychiatric-related Behaviors that are Modulated by Lithium and Stress

Leussis, M., Berry-Scott, E., Saito, M., Jhuang, H., Haan, G., Alkan, O., Luce, C., Madison, J., Sklar, P., Serre, T., Root, D., Petryshen, T.

Biological Psychiatry , 2012 (article)

Prepublication Article Abstract [BibTex]

Prepublication Article Abstract [BibTex]


Thumb xl icptnra1
Segmentation of Vessel Geometries from Medical Images Using GPF Deformable Model

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

In International Conference on Pattern Recognition Applications and Methods, 2012 (inproceedings)

Abstract
We present a method for the reconstruction of vascular geometries from medical images. Image denoising is performed using vessel enhancing diffusion, which can smooth out image noise and enhance vessel structures. The Canny edge detection technique which produces object edges with single pixel width is used for accurate detection of the lumen boundaries. The image gradients are then used to compute the geometric potential field which gives a global representation of the geometric configuration. The deformable model uses a regional constraint to suppress calcified regions for accurate segmentation of the vessel geometries. The proposed framework show high accuracy when applied to the segmentation of the carotid arteries from CT images.

[BibTex]

[BibTex]


Thumb xl tseb1
Scan-Based Flow Modelling in Human Upper Airways

Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo

In Patient-Specific Modeling in Tomorrow’s Medicine, pages: 241 - 280, 0, (Editors: Amit Gefen), Springer, 2012 (inbook)

[BibTex]

[BibTex]


Thumb xl superfloxel
SuperFloxels: A Mid-Level Representation for Video Sequences

Ravichandran, A., Wang, C., Raptis, M., Soatto, S.

In Analysis and Retrieval of Tracked Events and Motion in Imagery Streams Workshop (ARTEMIS) (in conjunction with ECCV 2012), 2012 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl smcfv1
Implicit Active Contours for N-Dimensional Biomedical Image Segmentation

Si Yong Yeo

In IEEE International Conference on Systems, Man, and Cybernetics, pages: 2855 - 2860, 2012 (inproceedings)

Abstract
The segmentation of shapes from biomedical images has a wide range of uses such as image based modelling and bioimage analysis. In this paper, an active contour model is proposed for the segmentation of N-dimensional biomedical images. The proposed model uses a curvature smoothing flow and an image attraction force derived from the interactions between the geometries of the active contour model and the image objects. The active contour model is formulated using the level set method so as to handle topological changes automatically. The magnitude and orientation of the image attraction force is based on the relative geometric configurations between the active contour model and the image object boundaries. The vector force field is therefore dynamic, and the active contour model can propagate through narrow structures to segment complex shapes efficiently. The proposed model utilizes pixel interactions across the image domain, which gives a coherent representation of the image object shapes. This allows the active contour model to be robust to image noise and weak object edges. The proposed model is compared against widely used active contour models in the segmentation of anatomical shapes from biomedical images. It is shown that the proposed model has several advantages over existing techniques and can be used for the segmentation of biomedical images efficiently.

[BibTex]

[BibTex]


Thumb xl cells
Interactive Object Detection

Yao, A., Gall, J., Leistner, C., van Gool, L.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 3242-3249, IEEE, Providence, RI, USA, 2012 (inproceedings)

video pdf Project Page [BibTex]

video pdf Project Page [BibTex]


Thumb xl headpose
Real Time 3D Head Pose Estimation: Recent Achievements and Future Challenges

Fanelli, G., Gall, J., van Gool, L.

In 5th International Symposium on Communications, Control and Signal Processing (ISCCSP), 2012 (inproceedings)

data and code pdf Project Page [BibTex]

data and code pdf Project Page [BibTex]


Thumb xl hands
Motion Capture of Hands in Action using Discriminative Salient Points

Ballan, L., Taneja, A., Gall, J., van Gool, L., Pollefeys, M.

In European Conference on Computer Vision (ECCV), 7577, pages: 640-653, LNCS, Springer, 2012 (inproceedings)

data video pdf supplementary Project Page [BibTex]

data video pdf supplementary Project Page [BibTex]


Thumb xl selfsimilarity small
Sparsity Potentials for Detecting Objects with the Hough Transform

Razavi, N., Alvar, N., Gall, J., van Gool, L.

In British Machine Vision Conference (BMVC), pages: 11.1-11.10, (Editors: Bowden, Richard and Collomosse, John and Mikolajczyk, Krystian), BMVA Press, 2012 (inproceedings)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


Thumb xl multiclasshf
An Introduction to Random Forests for Multi-class Object Detection

Gall, J., Razavi, N., van Gool, L.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 243-263, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

code code for Hough forest publisher's site pdf Project Page [BibTex]

code code for Hough forest publisher's site pdf Project Page [BibTex]


Thumb xl metricpose
Metric Learning from Poses for Temporal Clustering of Human Motion

L’opez-M’endez, A., Gall, J., Casas, J., van Gool, L.

In British Machine Vision Conference (BMVC), pages: 49.1-49.12, (Editors: Bowden, Richard and Collomosse, John and Mikolajczyk, Krystian), BMVA Press, 2012 (inproceedings)

video pdf Project Page Project Page [BibTex]

video pdf Project Page Project Page [BibTex]


Thumb xl objectproposal
Local Context Priors for Object Proposal Generation

Ristin, M., Gall, J., van Gool, L.

In Asian Conference on Computer Vision (ACCV), 7724, pages: 57-70, LNCS, Springer-Verlag, 2012 (inproceedings)

pdf DOI Project Page [BibTex]

pdf DOI Project Page [BibTex]


Thumb xl kinectbookchap
Home 3D body scans from noisy image and range data

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

In Consumer Depth Cameras for Computer Vision: Research Topics and Applications, pages: 99-118, 6, (Editors: Andrea Fossati and Juergen Gall and Helmut Grabner and Xiaofeng Ren and Kurt Konolige), Springer-Verlag, 2012 (incollection)

Project Page [BibTex]

Project Page [BibTex]


Thumb xl cvprlayers12crop
Layered segmentation and optical flow estimation over time

Sun, D., Sudderth, E., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1768-1775, IEEE, 2012 (inproceedings)

Abstract
Layered models provide a compelling approach for estimating image motion and segmenting moving scenes. Previous methods, however, have failed to capture the structure of complex scenes, provide precise object boundaries, effectively estimate the number of layers in a scene, or robustly determine the depth order of the layers. Furthermore, previous methods have focused on optical flow between pairs of frames rather than longer sequences. We show that image sequences with more frames are needed to resolve ambiguities in depth ordering at occlusion boundaries; temporal layer constancy makes this feasible. Our generative model of image sequences is rich but difficult to optimize with traditional gradient descent methods. We propose a novel discrete approximation of the continuous objective in terms of a sequence of depth-ordered MRFs and extend graph-cut optimization methods with new “moves” that make joint layer segmentation and motion estimation feasible. Our optimizer, which mixes discrete and continuous optimization, automatically determines the number of layers and reasons about their depth ordering. We demonstrate the value of layered models, our optimization strategy, and the use of more than two frames on both the Middlebury optical flow benchmark and the MIT layer segmentation benchmark.

pdf sup mat poster Project Page Project Page [BibTex]

pdf sup mat poster Project Page Project Page [BibTex]


Thumb xl imavis2012
Natural Metrics and Least-Committed Priors for Articulated Tracking

Soren Hauberg, Stefan Sommer, Kim S. Pedersen

Image and Vision Computing, 30(6-7):453-461, Elsevier, 2012 (article)

Publishers site Code PDF [BibTex]

Publishers site Code PDF [BibTex]


Thumb xl bookcdc4cv
Consumer Depth Cameras for Computer Vision - Research Topics and Applications

Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K.

Advances in Computer Vision and Pattern Recognition, Springer, 2012 (book)

workshop publisher's site [BibTex]

workshop publisher's site [BibTex]


Thumb xl amdo2012v2
Spatial Measures between Human Poses for Classification and Understanding

Soren Hauberg, Kim S. Pedersen

In Articulated Motion and Deformable Objects, 7378, pages: 26-36, LNCS, (Editors: Perales, Francisco J. and Fisher, Robert B. and Moeslund, Thomas B.), Springer Berlin Heidelberg, 2012 (inproceedings)

Publishers site Project Page [BibTex]

Publishers site Project Page [BibTex]


Thumb xl nips teaser
A Geometric Take on Metric Learning

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

In Advances in Neural Information Processing Systems (NIPS) 25, pages: 2033-2041, (Editors: P. Bartlett and F.C.N. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberger), MIT Press, 2012 (inproceedings)

Abstract
Multi-metric learning techniques learn local metric tensors in different parts of a feature space. With such an approach, even simple classifiers can be competitive with the state-of-the-art because the distance measure locally adapts to the structure of the data. The learned distance measure is, however, non-metric, which has prevented multi-metric learning from generalizing to tasks such as dimensionality reduction and regression in a principled way. We prove that, with appropriate changes, multi-metric learning corresponds to learning the structure of a Riemannian manifold. We then show that this structure gives us a principled way to perform dimensionality reduction and regression according to the learned metrics. Algorithmically, we provide the first practical algorithm for computing geodesics according to the learned metrics, as well as algorithms for computing exponential and logarithmic maps on the Riemannian manifold. Together, these tools let many Euclidean algorithms take advantage of multi-metric learning. We illustrate the approach on regression and dimensionality reduction tasks that involve predicting measurements of the human body from shape data.

PDF Youtube Suppl. material Poster Project Page [BibTex]

PDF Youtube Suppl. material Poster Project Page [BibTex]

1999


Thumb xl bildschirmfoto 2013 01 14 um 09.07.06
Edges as outliers: Anisotropic smoothing using local image statistics

Black, M. J., Sapiro, G.

In Scale-Space Theories in Computer Vision, Second Int. Conf., Scale-Space ’99, pages: 259-270, LNCS 1682, Springer, Corfu, Greece, September 1999 (inproceedings)

Abstract
Edges are viewed as statistical outliers with respect to local image gradient magnitudes. Within local image regions we compute a robust statistical measure of the gradient variation and use this in an anisotropic diffusion framework to determine a spatially varying "edge-stopping" parameter σ. We show how to determine this parameter for two edge-stopping functions described in the literature (Perona-Malik and the Tukey biweight). Smoothing of the image is related the local texture and in regions of low texture, small gradient values may be treated as edges whereas in regions of high texture, large gradient magnitudes are necessary before an edge is preserved. Intuitively these results have similarities with human perceptual phenomena such as masking and "popout". Results are shown on a variety of standard images.

pdf [BibTex]

1999

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 07 um 12.35.15
Probabilistic detection and tracking of motion discontinuities

(Marr Prize, Honorable Mention)

Black, M. J., Fleet, D. J.

In Int. Conf. on Computer Vision, ICCV-99, pages: 551-558, ICCV, Corfu, Greece, September 1999 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 09.38.15
Parameterized modeling and recognition of activities

Yacoob, Y., Black, M. J.

Computer Vision and Image Understanding, 73(2):232-247, 1999 (article)

Abstract
In this paper we consider a class of human activities—atomic activities—which can be represented as a set of measurements over a finite temporal window (e.g., the motion of human body parts during a walking cycle) and which has a relatively small space of variations in performance. A new approach for modeling and recognition of atomic activities that employs principal component analysis and analytical global transformations is proposed. The modeling of sets of exemplar instances of activities that are similar in duration and involve similar body part motions is achieved by parameterizing their representation using principal component analysis. The recognition of variants of modeled activities is achieved by searching the space of admissible parameterized transformations that these activities can undergo. This formulation iteratively refines the recognition of the class to which the observed activity belongs and the transformation parameters that relate it to the model in its class. We provide several experiments on recognition of articulated and deformable human motions from image motion parameters.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.12.47
Explaining optical flow events with parameterized spatio-temporal models

Black, M. J.

In IEEE Proc. Computer Vision and Pattern Recognition, CVPR’99, pages: 326-332, IEEE, Fort Collins, CO, 1999 (inproceedings)

pdf video [BibTex]

pdf video [BibTex]


Thumb xl paircover
Artscience Sciencart

Black, M. J., Levy, D., PamelaZ,

In Art and Innovation: The Xerox PARC Artist-in-Residence Program, pages: 244-300, (Editors: Harris, C.), MIT-Press, 1999 (incollection)

abstract [BibTex]

abstract [BibTex]