Twist Based Acquisition and Tracking of Animal and Human Kinematics

Bregler, Christoph; Malik, Jitendra; Pullen, Katherine

doi:10.1023/b:visi.0000011203.00237.9b

Cited by 173 publications

(102 citation statements)

References 25 publications

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“…(2). A well known difficulty is that one can only recover noisy and cluttered image contours and, therefore, the error function should be able to cope with this problem.…”

Section: Fitting Extremal Contours To Imagesmentioning

confidence: 99%

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Tracking with the Kinematics of Extremal Contours

Knossow

Ronfard

Horaud

et al. 2006

Computer Vision – ACCV 2006

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Abstract. This paper addresses the problem of articulated motion tracking from image sequences. We describe a method that relies on an explicit parameterization of the extremal contours in terms of the joint parameters of an associated kinematic model. The latter allows us to predict the extremal contours from the body-part primitives of an articulated model and to compare them with observed image contours. The error function that measures the discrepancy between observed contours and predicted contours is minimized using an analytical expression of the Jacobian that maps joint velocities onto contour velocities. In practice we model people both by their geometry (truncated elliptical cones) and with their articulated structure -a kinematic model with 40 rotational degrees of freedom. We observe image data gathered with several synchronized cameras. The tracker has been successfully applied to image sequences gathered at 30 frames/second.

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“…(2). A well known difficulty is that one can only recover noisy and cluttered image contours and, therefore, the error function should be able to cope with this problem.…”

Section: Fitting Extremal Contours To Imagesmentioning

confidence: 99%

“…One approach extracts image features that can be used in the same way as markers, such as texture [2] or point features [3]. Those methods can be implemented in a straightforward manner since they have an explicit differential model of the kinematics, and the latter can be inverted using non-linear least squares methods.…”

Section: Introductionmentioning

confidence: 99%

Tracking with the Kinematics of Extremal Contours

Knossow

Ronfard

Horaud

et al. 2006

Computer Vision – ACCV 2006

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“…Ju et al in [28] extended the cardboard people model to articulated motion estimation for multi-layer framework. The articulated layers models has subsequently been used in a number of papers [29]- [33] and articulation constraints, including constraints on angular velocity and acceleration, have been used for 3D model estimation as well [34]- [40]. Bregler et al in [34], [35] demonstrate recovery of 3D articulated motion using twists and exponential maps.…”

Section: Related Workmentioning

confidence: 99%

“…The articulated layers models has subsequently been used in a number of papers [29]- [33] and articulation constraints, including constraints on angular velocity and acceleration, have been used for 3D model estimation as well [34]- [40]. Bregler et al in [34], [35] demonstrate recovery of 3D articulated motion using twists and exponential maps. In their formulation, twists are modeled as revolute joints anchored at articulations, that are then propagated to the next time-step under the assumption of isotropic Gaussian noise.…”

Section: Related Workmentioning

confidence: 99%

Linearized Motion Estimation for Articulated Planes

Datta

Sheikh

Kanade

2011

IEEE Trans. Pattern Anal. Mach. Intell.

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Abstract-In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforce articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes and motion estimation of triangulated meshes.

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“…Fitting articulated skeletons to human figures leads to high-dimensional optimization problems with complex energy landscapes. Bayesian approaches, from classic Kalman filtering [14,13] to various flavours of particle filtering [15,16] are the majority, but it is not often easy to incorporate anatomical constraints, parallelize the algorithms, devise suitable observation models as pdf, and devise realistic body motion models.…”

Section: Related Workmentioning

confidence: 99%

Human Body Posture via Hierarchical Evolutionary Optimization

Robertson¹,

Trucco²

2006

Procedings of the British Machine Vision Conference 2006

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This paper presents an evolutionary approach to estimating upper-body posture from multi-view markerless sequences. We fit a 24-dof skeleton model to sparse 3-D stereo data from an array of cameras. We use a particle swarm optimization algorithm which is intrinsically parallel, can incorporate constraints and does not require motion models. We subdivide the high-dimensional search space based on limb dynamics from application sequences and perform hierarchical fitting from the least to the most uncertain body parts. We show experimentally the advantages of this scheme against non-hierarchical optimization in terms of sharper error decrease. We report results with 3-D scanner data of a model human and noisy, calibrated stereo disparity maps of a real videoconferencing scene.

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Twist Based Acquisition and Tracking of Animal and Human Kinematics

Cited by 173 publications

References 25 publications

Tracking with the Kinematics of Extremal Contours

Tracking with the Kinematics of Extremal Contours

Linearized Motion Estimation for Articulated Planes

Human Body Posture via Hierarchical Evolutionary Optimization

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