Results 1 - 10
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63
Motion capture using joint skeleton tracking and surface estimation
- IN IEEE CONF. ON COMPUTER VISION AND PATTERN RECOGNITION
, 2009
"... This paper proposes a method for capturing the performance of a human or an animal from a multi-view video sequence. Given an articulated template model and silhouettes from a multi-view image sequence, our approach recovers not only the movement of the skeleton, but also the possibly non-rigid temp ..."
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Cited by 78 (16 self)
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This paper proposes a method for capturing the performance of a human or an animal from a multi-view video sequence. Given an articulated template model and silhouettes from a multi-view image sequence, our approach recovers not only the movement of the skeleton, but also the possibly non-rigid temporal deformation of the 3D surface. While large scale deformations or fast movements are captured by the skeleton pose and approximate surface skinning, true small scale deformations or non-rigid garment motion are captured by fitting the surface to the silhouette. We further propose a novel optimization scheme for skeleton-based pose estimation that exploits the skeleton’s tree structure to split the optimization problem into a local one and a lower dimensional global one. We show on various sequences that our approach can capture the 3D motion of animals and humans accurately even in the case of rapid movements and wide apparel like skirts.
Marker-less Deformable Mesh Tracking for Human Shape and Motion Capture
"... We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead of relying on kinematic skeletons, as traditional motion capture methods, our approach uses a deformable high-quality mesh of a human as scene ..."
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Cited by 56 (6 self)
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We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead of relying on kinematic skeletons, as traditional motion capture methods, our approach uses a deformable high-quality mesh of a human as scene representation. It jointly uses an imagebased 3D correspondence estimation algorithm and a fast Laplacian mesh deformation scheme to capture both motion and surface deformation of the actor from the input video footage. As opposed to many related methods, our algorithm can track people wearing wide apparel, it can straightforwardly be applied to any type of subject, e.g. animals, and it preserves the connectivity of the mesh over time. We demonstrate the performance of our approach using synthetic and captured real-world video sequences and validate its accuracy by comparison to the ground truth. 1.
Estimating Human Shape and Pose from a Single Image
"... We describe a solution to the challenging problem of estimating human body shape from a single photograph or painting. Our approach computes shape and pose parameters of a 3D human body model directly from monocular image cues and advances the state of the art in several directions. First, given a u ..."
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Cited by 52 (6 self)
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We describe a solution to the challenging problem of estimating human body shape from a single photograph or painting. Our approach computes shape and pose parameters of a 3D human body model directly from monocular image cues and advances the state of the art in several directions. First, given a user-supplied estimate of the subject’s height and a few clicked points on the body we estimate an initial 3D articulated body pose and shape. Second, using this initial guess we generate a tri-map of regions inside, outside and on the boundary of the human, which is used to segment the image using graph cuts. Third, we learn a low-dimensional linear model of human shape in which variations due to height are concentrated along a single dimension, enabling height-constrained estimation of body shape. Fourth, we formulate the problem of parametric human shape from shading. We estimate the body pose, shape and reflectance as well as the scene lighting that produces a synthesized body that robustly matches the image evidence. Quantitative experiments demonstrate how smooth shading provides powerful constraints on human shape. We further demonstrate a novel application in which we extract 3D human models from archival photographs and paintings. 1.
Hierarchical Implicit Surface Joint Limits for Human Body Tracking
- In Proc. ECCV
, 2004
"... To increase the reliability of existing human motion tracking algorithms, we propose a method for imposing limits on the underlying hierarchical joint structures in a way that is true to life. Unlike most existing approaches, we explicitly represent dependencies between the various degrees of fre ..."
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Cited by 47 (5 self)
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To increase the reliability of existing human motion tracking algorithms, we propose a method for imposing limits on the underlying hierarchical joint structures in a way that is true to life. Unlike most existing approaches, we explicitly represent dependencies between the various degrees of freedom and derive these limits from actual experimental data.
3D human body tracking using deterministic temporal motion models
- In ECCV
, 2004
"... Abstract. There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and seek to avoid becoming trapped into local minima by considering multiple hypotheses, which typically requires exponentiall ..."
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Cited by 44 (8 self)
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Abstract. There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and seek to avoid becoming trapped into local minima by considering multiple hypotheses, which typically requires exponentially large amounts of computation as the number of degrees of freedom increases. By contrast, in this paper, we use temporal motion models based on Principal Component Analysis to formulate the tracking problem as one of minimizing differentiable objective functions. The differential structure of these functions is rich enough to yield good convergence properties using a deterministic optimization scheme at a much reduced computational cost. Furthermore, by using a multi-activity database, we can partially overcome one of the major limitations of approaches that rely on motion models, namely the fact they are limited to one single type of motion. We will demonstrate the effectiveness of the proposed approach by using it to fit full-body models to stereo data of people walking and running and whose quality is too low to yield satisfactory results without motion models. 1
Temporal motion models for monocular and multiview 3D human body tracking
- CVIU
"... We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable criterion whose differential structure is rich enough for optimization to be accomplished via hill-climbing. This avoids ..."
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Cited by 36 (4 self)
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We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable criterion whose differential structure is rich enough for optimization to be accomplished via hill-climbing. This avoids the computational expense of Monte Carlo methods, while yielding good results under challenging conditions. To demonstrate the generality of the approach we show that we can learn and track cyclic motions such as walking and running, as well as acyclic motions such as a golf swing. We also show results from both monocular and multi-camera tracking. Finally, we provide results with a motion model learned from multiple activities, and show how this models might be used for recognition.
Hand Motion from 3D Point Trajectories and a Smooth Surface Model
- 8TH EUROPEAN CONFERENCE ON COMPUTER VISION. VOLUME I OF LNCS 3021
, 2004
"... A method is proposed to track the full hand motion from 3D points on the surface of the hand that were reconstructed and tracked using a stereoscopic set of cameras. This approach combines the advantages of previous methods that use 2D motion (e.g. optical flow), and those that use a 3D reconstr ..."
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Cited by 35 (8 self)
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A method is proposed to track the full hand motion from 3D points on the surface of the hand that were reconstructed and tracked using a stereoscopic set of cameras. This approach combines the advantages of previous methods that use 2D motion (e.g. optical flow), and those that use a 3D reconstruction at each time frame to capture the hand motion. Matching either contours or a 3D reconstruction against a 3D hand model is usually very difficult due to self-occlusions and the locally-cylindrical structure of each phalanx in the model, but our use of 3D point trajectories constrains the motion and overcomes these problems. Our tracking
3D Tracking for Gait Characterization and Recognition
- In: Proc. IEEE Automatic Face and Gesture Recognition, Seoul, Korea
, 2004
"... We propose an approach to gait analysis that relies on fitting 3-D temporal motion models to synchronized video sequences. These models allow us not only to track but also to recover motion parameters that can be used to recognize people and characterize their style. Because our method is robust... ..."
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Cited by 24 (1 self)
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We propose an approach to gait analysis that relies on fitting 3-D temporal motion models to synchronized video sequences. These models allow us not only to track but also to recover motion parameters that can be used to recognize people and characterize their style. Because our method is robust...
Rigid and articulated point registration with expectation conditional maximization
- IEEE Transactions on Pattern Analysis and Machine Intelligence
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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Cited by 24 (5 self)
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Accurate 3D Pose Estimation From a Single Depth Image
"... This paper presents a novel system to estimate body pose configuration from a single depth map. It combines both pose detection and pose refinement. The input depth map is matched with a set of pre-captured motion exemplars to generate a body configuration estimation, as well as semantic labeling of ..."
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Cited by 22 (2 self)
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This paper presents a novel system to estimate body pose configuration from a single depth map. It combines both pose detection and pose refinement. The input depth map is matched with a set of pre-captured motion exemplars to generate a body configuration estimation, as well as semantic labeling of the input point cloud. The initial estimation is then refined by directly fitting the body configuration with the observation (e.g., the input depth). In addition to the new system architecture, our other contributions include modifying a point cloud smoothing technique to deal with very noisy input depth maps, a point cloud alignment and pose search algorithm that is view-independent and efficient. Experiments on a public dataset show that our approach achieves significantly higher accuracy than previous state-of-art methods. 1.