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25 results (View BibTeX file of all listed publications)

2017

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Human Shape Estimation using Statistical Body Models

Loper, M. M.

University of Tübingen, May 2017 (thesis)

Abstract
Human body estimation methods transform real-world observations into predictions about human body state. These estimation methods benefit a variety of health, entertainment, clothing, and ergonomics applications. State may include pose, overall body shape, and appearance. Body state estimation is underconstrained by observations; ambiguity presents itself both in the form of missing data within observations, and also in the form of unknown correspondences between observations. We address this challenge with the use of a statistical body model: a data-driven virtual human. This helps resolve ambiguity in two ways. First, it fills in missing data, meaning that incomplete observations still result in complete shape estimates. Second, the model provides a statistically-motivated penalty for unlikely states, which enables more plausible body shape estimates. Body state inference requires more than a body model; we therefore build obser- vation models whose output is compared with real observations. In this thesis, body state is estimated from three types of observations: 3D motion capture markers, depth and color images, and high-resolution 3D scans. In each case, a forward process is proposed which simulates observations. By comparing observations to the results of the forward process, state can be adjusted to minimize the difference between simulated and observed data. We use gradient-based methods because they are critical to the precise estimation of state with a large number of parameters. The contributions of this work include three parts. First, we propose a method for the estimation of body shape, nonrigid deformation, and pose from 3D markers. Second, we present a concise approach to differentiating through the rendering process, with application to body shape estimation. And finally, we present a statistical body model trained from human body scans, with state-of-the-art fidelity, good runtime performance, and compatibility with existing animation packages.

Official Version [BibTex]

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Learning Inference Models for Computer Vision

Jampani, V.

MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)

Abstract
Computer vision can be understood as the ability to perform 'inference' on image data. Breakthroughs in computer vision technology are often marked by advances in inference techniques, as even the model design is often dictated by the complexity of inference in them. This thesis proposes learning based inference schemes and demonstrates applications in computer vision. We propose techniques for inference in both generative and discriminative computer vision models. Despite their intuitive appeal, the use of generative models in vision is hampered by the difficulty of posterior inference, which is often too complex or too slow to be practical. We propose techniques for improving inference in two widely used techniques: Markov Chain Monte Carlo (MCMC) sampling and message-passing inference. Our inference strategy is to learn separate discriminative models that assist Bayesian inference in a generative model. Experiments on a range of generative vision models show that the proposed techniques accelerate the inference process and/or converge to better solutions. A main complication in the design of discriminative models is the inclusion of prior knowledge in a principled way. For better inference in discriminative models, we propose techniques that modify the original model itself, as inference is simple evaluation of the model. We concentrate on convolutional neural network (CNN) models and propose a generalization of standard spatial convolutions, which are the basic building blocks of CNN architectures, to bilateral convolutions. First, we generalize the existing use of bilateral filters and then propose new neural network architectures with learnable bilateral filters, which we call `Bilateral Neural Networks'. We show how the bilateral filtering modules can be used for modifying existing CNN architectures for better image segmentation and propose a neural network approach for temporal information propagation in videos. Experiments demonstrate the potential of the proposed bilateral networks on a wide range of vision tasks and datasets. In summary, we propose learning based techniques for better inference in several computer vision models ranging from inverse graphics to freely parameterized neural networks. In generative vision models, our inference techniques alleviate some of the crucial hurdles in Bayesian posterior inference, paving new ways for the use of model based machine learning in vision. In discriminative CNN models, the proposed filter generalizations aid in the design of new neural network architectures that can handle sparse high-dimensional data as well as provide a way for incorporating prior knowledge into CNNs.

pdf [BibTex]

Jampani, V. Learning Inference Models for Computer Vision MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)

pdf [BibTex]

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Capturing Hand-Object Interaction and Reconstruction of Manipulated Objects

Tzionas, D.

University of Bonn, 2017 (phdthesis)

Abstract
Hand motion capture with an RGB-D sensor gained recently a lot of research attention, however, even most recent approaches focus on the case of a single isolated hand. We focus instead on hands that interact with other hands or with a rigid or articulated object. Our framework successfully captures motion in such scenarios by combining a generative model with discriminatively trained salient points, collision detection and physics simulation to achieve a low tracking error with physically plausible poses. All components are unified in a single objective function that can be optimized with standard optimization techniques. We initially assume a-priori knowledge of the object's shape and skeleton. In case of unknown object shape there are existing 3d reconstruction methods that capitalize on distinctive geometric or texture features. These methods though fail for textureless and highly symmetric objects like household articles, mechanical parts or toys. We show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of such objects and we fuse the rich additional information of hands into a 3d reconstruction pipeline. Finally, although shape reconstruction is enough for rigid objects, there is a lack of tools that build rigged models of articulated objects that deform realistically using RGB-D data. We propose a method that creates a fully rigged model consisting of a watertight mesh, embedded skeleton and skinning weights by employing a combination of deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow.

Thesis link (url) Project Page [BibTex]

2013

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Puppet Flow

Zuffi, S., Black, M. J.

(7), Max Planck Institute for Intelligent Systems, October 2013 (techreport)

Abstract
We introduce Puppet Flow (PF), a layered model describing the optical flow of a person in a video sequence. We consider video frames composed by two layers: a foreground layer corresponding to a person, and background. We model the background as an affine flow field. The foreground layer, being a moving person, requires reasoning about the articulated nature of the human body. We thus represent the foreground layer with the Deformable Structures model (DS), a parametrized 2D part-based human body representation. We call the motion field defined through articulated motion and deformation of the DS model, a Puppet Flow. By exploiting the DS representation, Puppet Flow is a parametrized optical flow field, where parameters are the person's pose, gender and body shape.

pdf Project Page Project Page [BibTex]

2013

Zuffi, S., Black, M. J. Puppet Flow (7), Max Planck Institute for Intelligent Systems, October 2013 (techreport)

pdf Project Page Project Page [BibTex]

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D2.1.4 RoCKIn@Work - Innovation in Mobile Industrial Manipulation Competition Design, Rule Book, and Scenario Construction

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

(FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics in Europe and to demonstrate the innovation potential of robotics applications for solving societal challenges and improving the competitiveness of Europe in the global markets. In order to achieve these objectives, RoCKIn develops two competitions, one for domestic service robots (RoCKIn@Home) and one for industrial robots in factories (RoCKIn-@Work). These competitions are designed around challenges that are based on easy-to-communicate and convincing user stories, which catch the interest of both the general public and the scientifc community. The latter is in particular interested in solving open scientific challenges and to thoroughly assess, compare, and evaluate the developed approaches with competing ones. To allow this to happen, the competitions are designed to meet the requirements of benchmarking procedures and good experimental methods. The integration of benchmarking technology with the competition concept is one of the main objectives of RoCKIn. This document describes the first version of the RoCKIn@Work competition, which will be held for the first time in 2014. The first chapter of the document gives a brief overview, outlining the purpose and objective of the competition, the methodological approach taken by the RoCKIn project, the user story upon which the competition is based, the structure and organization of the competition, and the commonalities and differences with the RoboCup@Work competition, which served as inspiration for RoCKIn@Work. The second chapter provides details on the user story and analyzes the scientific and technical challenges it poses. Consecutive chapters detail the competition scenario, the competition design, and the organization of the competition. The appendices contain information on a library of functionalities, which we believe are needed, or at least useful, for building competition entries, details on the scenario construction, and a detailed account of the benchmarking infrastructure needed — and provided by RoCKIn.

[BibTex]

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schneider, S. D2.1.4 RoCKIn@Work - Innovation in Mobile Industrial Manipulation Competition Design, Rule Book, and Scenario Construction (FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

[BibTex]

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D2.1.1 RoCKIn@Home - A Competition for Domestic Service Robots Competition Design, Rule Book, and Scenario Construction

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

(FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics in Europe and to demonstrate the innovation potential of robotics applications for solving societal challenges and improving the competitiveness of Europe in the global markets. In order to achieve these objectives, RoCKIn develops two competitions, one for domestic service robots (RoCKIn@Home) and one for industrial robots in factories (RoCKIn-@Work). These competitions are designed around challenges that are based on easy-to-communicate and convincing user stories, which catch the interest of both the general public and the scientifc community. The latter is in particular interested in solving open scientific challenges and to thoroughly assess, compare, and evaluate the developed approaches with competing ones. To allow this to happen, the competitions are designed to meet the requirements of benchmarking procedures and good experimental methods. The integration of benchmarking technology with the competition concept is one of the main objectives of RoCKIn. This document describes the first version of the RoCKIn@Home competition, which will be held for the first time in 2014. The first chapter of the document gives a brief overview, outlining the purpose and objective of the competition, the methodological approach taken by the RoCKIn project, the user story upon which the competition is based, the structure and organization of the competition, and the commonalities and differences with the RoboCup@Home competition, which served as inspiration for RoCKIn@Home. The second chapter provides details on the user story and analyzes the scientific and technical challenges it poses. Consecutive chapters detail the competition scenario, the competition design, and the organization of the competition. The appendices contain information on a library of functionalities, which we believe are needed, or at least useful, for building competition entries, details on the scenario construction, and a detailed account of the benchmarking infrastructure needed — and provided by RoCKIn.

[BibTex]

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schneider, S. D2.1.1 RoCKIn@Home - A Competition for Domestic Service Robots Competition Design, Rule Book, and Scenario Construction (FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

[BibTex]

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Statistics on Manifolds with Applications to Modeling Shape Deformations

Freifeld, O.

Brown University, August 2013 (phdthesis)

Abstract
Statistical models of non-rigid deformable shape have wide application in many fi elds, including computer vision, computer graphics, and biometry. We show that shape deformations are well represented through nonlinear manifolds that are also matrix Lie groups. These pattern-theoretic representations lead to several advantages over other alternatives, including a principled measure of shape dissimilarity and a natural way to compose deformations. Moreover, they enable building models using statistics on manifolds. Consequently, such models are superior to those based on Euclidean representations. We demonstrate this by modeling 2D and 3D human body shape. Shape deformations are only one example of manifold-valued data. More generally, in many computer-vision and machine-learning problems, nonlinear manifold representations arise naturally and provide a powerful alternative to Euclidean representations. Statistics is traditionally concerned with data in a Euclidean space, relying on the linear structure and the distances associated with such a space; this renders it inappropriate for nonlinear spaces. Statistics can, however, be generalized to nonlinear manifolds. Moreover, by respecting the underlying geometry, the statistical models result in not only more e ffective analysis but also consistent synthesis. We go beyond previous work on statistics on manifolds by showing how, even on these curved spaces, problems related to modeling a class from scarce data can be dealt with by leveraging information from related classes residing in di fferent regions of the space. We show the usefulness of our approach with 3D shape deformations. To summarize our main contributions: 1) We de fine a new 2D articulated model -- more expressive than traditional ones -- of deformable human shape that factors body-shape, pose, and camera variations. Its high realism is obtained from training data generated from a detailed 3D model. 2) We defi ne a new manifold-based representation of 3D shape deformations that yields statistical deformable-template models that are better than the current state-of-the- art. 3) We generalize a transfer learning idea from Euclidean spaces to Riemannian manifolds. This work demonstrates the value of modeling manifold-valued data and their statistics explicitly on the manifold. Specifi cally, the methods here provide new tools for shape analysis.

pdf Project Page [BibTex]

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D1.1 Specification of General Features of Scenarios and Robots for Benchmarking Through Competitions

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

(FP7-ICT-601012 Revision 1.0), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, July 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics and the innovation potential of robotics applications. From these objectives several requirements for the work performed in RoCKIn can be derived: The RoCKIn competitions must start from convincing, easy-to-communicate user stories, that catch the attention of relevant stakeholders, the media, and the crowd. The user stories play the role of a mid- to long-term vision for a competition. Preferably, the user stories address economic, societal, or environmental problems. The RoCKIn competitions must pose open scientific challenges of interest to sufficiently many researchers to attract existing and new teams of robotics researchers for participation in the competition. The competitions need to promise some suitable reward, such as recognition in the scientific community, publicity for a team’s work, awards, or prize money, to justify the effort a team puts into the development of a competition entry. The competitions should be designed in such a way that they reward general, scientifically sound solutions to the challenge problems; such general solutions should score better than approaches that work only in narrowly defined contexts and are considred over-engineered. The challenges motivating the RoCKIn competitions must be broken down into suitable intermediate goals that can be reached with a limited team effort until the next competition and the project duration. The RoCKIn competitions must be well-defined and well-designed, with comprehensive rule books and instructions for the participants in order to guarantee a fair competition. The RoCKIn competitions must integrate competitions with benchmarking in order to provide comprehensive feedback for the teams about the suitability of particular functional modules, their overall architecture, and system integration. This document takes the first steps towards the RoCKIn goals. After outlining our approach, we present several user stories for further discussion within the community. The main objectives of this document are to identify and document relevant scenario features and the tasks and functionalities subject for benchmarking in the competitions.

[BibTex]

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Fontana, G., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schiaffonati, V., Schneider, S. D1.1 Specification of General Features of Scenarios and Robots for Benchmarking Through Competitions (FP7-ICT-601012 Revision 1.0), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, July 2013 (techreport)

[BibTex]

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SocRob-MSL 2013 Team Description Paper for Middle Sized League

Messias, J., Ahmad, A., Reis, J., Serafim, M., Lima, P.

17th Annual RoboCup International Symposium 2013, July 2013 (techreport)

Abstract
This paper describes the status of the SocRob MSL robotic soccer team as required by the RoboCup 2013 qualification procedures. The team’s latest scientific and technical developments, since its last participation in RoboCup MSL, include further advances in cooperative perception; novel communication methods for distributed robotics; progressive deployment of the ROS middleware; improved localization through feature tracking and Mixture MCL; novel planning methods based on Petri nets and decision-theoretic frameworks; and hardware developments in ball-handling/kicking devices.

link (url) [BibTex]

Messias, J., Ahmad, A., Reis, J., Serafim, M., Lima, P. SocRob-MSL 2013 Team Description Paper for Middle Sized League 17th Annual RoboCup International Symposium 2013, July 2013 (techreport)

link (url) [BibTex]

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Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms

Geiger, A.

Karlsruhe Institute of Technology, Karlsruhe Institute of Technology, April 2013 (phdthesis)

Abstract
Visual 3D scene understanding is an important component in autonomous driving and robot navigation. Intelligent vehicles for example often base their decisions on observations obtained from video cameras as they are cheap and easy to employ. Inner-city intersections represent an interesting but also very challenging scenario in this context: The road layout may be very complex and observations are often noisy or even missing due to heavy occlusions. While Highway navigation and autonomous driving on simple and annotated intersections have already been demonstrated successfully, understanding and navigating general inner-city crossings with little prior knowledge remains an unsolved problem. This thesis is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences. The model takes advantage of monocular information in the form of vehicle tracklets, vanishing lines and semantic labels. Additionally, the benefit of stereo features such as 3D scene flow and occupancy grids is investigated. Motivated by the impressive driving capabilities of humans, no further information such as GPS, lidar, radar or map knowledge is required. Experiments conducted on 113 representative intersection sequences show that the developed approach successfully infers the correct layout in a variety of difficult scenarios. To evaluate the importance of each feature cue, experiments with different feature combinations are conducted. Additionally, the proposed method is shown to improve object detection and object orientation estimation performance.

pdf [BibTex]

Geiger, A. Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms Karlsruhe Institute of Technology, Karlsruhe Institute of Technology, April 2013 (phdthesis)

pdf [BibTex]

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A Study of X-Ray Image Perception for Pneumoconiosis Detection

Jampani, V.

IIIT-Hyderabad, Hyderabad, India, January 2013 (mastersthesis)

Abstract
Pneumoconiosis is an occupational lung disease caused by the inhalation of industrial dust. Despite the increasing safety measures and better work place environments, pneumoconiosis is deemed to be the most common occupational disease in the developing countries like India and China. Screening and assessment of this disease is done through radiological observation of chest x-rays. Several studies have shown the significant inter and intra reader observer variation in the diagnosis of this disease, showing the complexity of the task and importance of the expertise in diagnosis. The present study is aimed at understanding the perceptual and cognitive factors affecting the reading of chest x-rays of pneumoconiosis patients. Understanding these factors helps in developing better image acquisition systems, better training regimen for radiologists and development of better computer aided diagnostic (CAD) systems. We used an eye tracking experiment to study the various factors affecting the assessment of this diffused lung disease. Specifically, we aimed at understanding the role of expertize, contralateral symmetric (CS) information present in chest x-rays on the diagnosis and the eye movements of the observers. We also studied the inter and intra observer fixation consistency along with the role of anatomical and bottom up saliency features in attracting the gaze of observers of different expertize levels, to get better insights into the effect of bottom up and top down visual saliency on the eye movements of observers. The experiment is conducted in a room dedicated to eye tracking experiments. Participants consisting of novices (3), medical students (12), residents (4) and staff radiologists (4) were presented with good quality PA chest X-rays, and were asked to give profusion ratings for each of the 6 lung zones. Image set consisting of 17 normal full chest x-rays and 16 single lung images are shown to the participants in random order. Time of the diagnosis and the eye movements are also recorded using a remote head free eye tracker. Results indicated that Expertise and CS play important roles in the diagnosis of pneumoconiosis. Novices and medical students are slow and inefficient whereas, residents and staff are quick and efficient. A key finding of our study is that the presence of CS information alone does not help improve diagnosis as much as learning how to use the information. This learning appears to be gained from focused training and years of experience. Hence, good training for radiologists and careful observation of each lung zone may improve the quality of diagnostic results. For residents, the eye scanning strategies play an important role in using the CS information present in chest radiographs; however, in staff radiologists, peripheral vision or higher-level cognitive processes seems to play role in using the CS information. There is a reasonably good inter and intra observer fixation consistency suggesting the use of similar viewing strategies. Experience is helping the observers to develop new visual strategies based on the image content so that they can quickly and efficiently assess the disease level. First few fixations seem to be playing an important role in choosing the visual strategy, appropriate for the given image. Both inter-rib and rib regions are given equal importance by the observers. Despite reading of chest x-rays being highly task dependent, bottom up saliency is shown to have played an important role in attracting the fixations of the observers. This role of bottom up saliency seems to be more in lower expertize groups compared to that of higher expertize groups. Both bottom up and top down influence of visual fixations seems to change with time. The relative role of top down and bottom up influences of visual attention is still not completely understood and it remains the part of future work. Based on our experimental results, we have developed an extended saliency model by combining the bottom up saliency and the saliency of lung regions in a chest x-ray. This new saliency model performed significantly better than bottom-up saliency in predicting the gaze of the observers in our experiment. Even though, the model is a simple combination of bottom-up saliency maps and segmented lung masks, this demonstrates that even basic models using simple image features can predict the fixations of the observers to a good accuracy. Experimental analysis suggested that the factors affecting the reading of chest x-rays of pneumoconiosis are complex and varied. A good understanding of these factors definitely helps in the development of better radiological screening of pneumoconiosis through improved training and also through the use of improved CAD tools. The presented work is an attempt to get insights into what these factors are and how they modify the behavior of the observers.

pdf [BibTex]

Jampani, V. A Study of X-Ray Image Perception for Pneumoconiosis Detection IIIT-Hyderabad, Hyderabad, India, January 2013 (mastersthesis)

pdf [BibTex]

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A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them

Sun, D., Roth, S., Black, M. J.

(CS-10-03), Brown University, Department of Computer Science, January 2013 (techreport)

pdf [BibTex]

Sun, D., Roth, S., Black, M. J. A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them (CS-10-03), Brown University, Department of Computer Science, January 2013 (techreport)

pdf [BibTex]

2012

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Virtual Human Bodies with Clothing and Hair: From Images to Animation

Guan, P.

Brown University, Department of Computer Science, December 2012 (phdthesis)

pdf [BibTex]

2012

Guan, P. Virtual Human Bodies with Clothing and Hair: From Images to Animation Brown University, Department of Computer Science, December 2012 (phdthesis)

pdf [BibTex]

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Coregistration: Supplemental Material

Hirshberg, D., Loper, M., Rachlin, E., Black, M. J.

(No. 4), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf [BibTex]

Hirshberg, D., Loper, M., Rachlin, E., Black, M. J. Coregistration: Supplemental Material (No. 4), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf [BibTex]

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Lie Bodies: A Manifold Representation of 3D Human Shape. Supplemental Material

Freifeld, O., Black, M. J.

(No. 5), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

Freifeld, O., Black, M. J. Lie Bodies: A Manifold Representation of 3D Human Shape. Supplemental Material (No. 5), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

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MPI-Sintel Optical Flow Benchmark: Supplemental Material

Butler, D. J., Wulff, J., Stanley, G. B., Black, M. J.

(No. 6), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

Butler, D. J., Wulff, J., Stanley, G. B., Black, M. J. MPI-Sintel Optical Flow Benchmark: Supplemental Material (No. 6), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

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From Pixels to Layers: Joint Motion Estimation and Segmentation

Sun, D.

Brown University, Department of Computer Science, July 2012 (phdthesis)

pdf [BibTex]

Sun, D. From Pixels to Layers: Joint Motion Estimation and Segmentation Brown University, Department of Computer Science, July 2012 (phdthesis)

pdf [BibTex]

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An Analysis of Successful Approaches to Human Pose Estimation

Lassner, C.

An Analysis of Successful Approaches to Human Pose Estimation, University of Augsburg, University of Augsburg, May 2012 (mastersthesis)

Abstract
The field of Human Pose Estimation is developing fast and lately leaped forward with the release of the Kinect system. That system reaches a very good perfor- mance for pose estimation using 3D scene information, however pose estimation from 2D color images is not solved reliably yet. There is a vast amount of pub- lications trying to reach this aim, but no compilation of important methods and solution strategies. The aim of this thesis is to fill this gap: it gives an introductory overview over important techniques by analyzing four current (2012) publications in detail. They are chosen such, that during their analysis many frequently used techniques for Human Pose Estimation can be explained. The thesis includes two introductory chapters with a definition of Human Pose Estimation and exploration of the main difficulties, as well as a detailed explanation of frequently used methods. A final chapter presents some ideas on how parts of the analyzed approaches can be recombined and shows some open questions that can be tackled in future work. The thesis is therefore a good entry point to the field of Human Pose Estimation and enables the reader to get an impression of the current state-of-the-art.

pdf [BibTex]

Lassner, C. An Analysis of Successful Approaches to Human Pose Estimation An Analysis of Successful Approaches to Human Pose Estimation, University of Augsburg, University of Augsburg, May 2012 (mastersthesis)

pdf [BibTex]

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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]

Soren Hauberg, Kim S. Pedersen HUMIM Software for Articulated Tracking (01/2012), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

Code PDF [BibTex]

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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]

Aasa Feragen, Mads Nielsen, Soren Hauberg, Pechin Lo, Marleen de Bruijne, Francois Lauze A geometric framework for statistics on trees (11/02), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

PDF [BibTex]

2008

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Infinite Kernel Learning

Gehler, P., Nowozin, S.

(178), Max Planck Institute, octomber 2008 (techreport)

project page pdf [BibTex]

2008

Gehler, P., Nowozin, S. Infinite Kernel Learning (178), Max Planck Institute, octomber 2008 (techreport)

project page pdf [BibTex]

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Incremental nonparametric Bayesian regression

Wood, F., Grollman, D. H., Heller, K. A., Jenkins, O. C., Black, M. J.

(CS-08-07), Brown University, Department of Computer Science, 2008 (techreport)

pdf [BibTex]

Wood, F., Grollman, D. H., Heller, K. A., Jenkins, O. C., Black, M. J. Incremental nonparametric Bayesian regression (CS-08-07), Brown University, Department of Computer Science, 2008 (techreport)

pdf [BibTex]

2006

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Implicit Wiener Series, Part II: Regularised estimation

Gehler, P., Franz, M.

(148), Max Planck Institute, 2006 (techreport)

pdf [BibTex]

2006

Gehler, P., Franz, M. Implicit Wiener Series, Part II: Regularised estimation (148), Max Planck Institute, 2006 (techreport)

pdf [BibTex]

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HumanEva: Synchronized video and motion capture dataset for evaluation of articulated human motion

Sigal, L., Black, M. J.

(CS-06-08), Brown University, Department of Computer Science, 2006 (techreport)

pdf abstract [BibTex]

Sigal, L., Black, M. J. HumanEva: Synchronized video and motion capture dataset for evaluation of articulated human motion (CS-06-08), Brown University, Department of Computer Science, 2006 (techreport)

pdf abstract [BibTex]

1996

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Mixture Models for Image Representation

Jepson, A., Black, M.

PRECARN ARK Project Technical Report ARK96-PUB-54, March 1996 (techreport)

Abstract
We consider the estimation of local greylevel image structure in terms of a layered representation. This type of representation has recently been successfully used to segment various objects from clutter using either optical ow or stereo disparity information. We argue that the same type of representation is useful for greylevel data in that it allows for the estimation of properties for each of several different components without prior segmentation. Our emphasis in this paper is on the process used to extract such a layered representation from a given image In particular we consider a variant of the EM algorithm for the estimation of the layered model and consider a novel technique for choosing the number of layers to use. We briefly consider the use of a simple version of this approach for image segmentation and suggest two potential applications to the ARK project

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1996

Jepson, A., Black, M. Mixture Models for Image Representation PRECARN ARK Project Technical Report ARK96-PUB-54, March 1996 (techreport)

pdf [BibTex]