Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction
We address the problem of body pose tracking in a scenario of multiple camera setup with the aim of recovering body motion robustly and accurately. The tracking is performed on three-dimensional (3D) space using 3D data, including colored volume and 3D optical flow, which are reconstructed at each t...
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sg-ntu-dr.10356-798842020-05-28T07:19:07Z Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction Zheng, Zhang Seah, Hock Soon School of Computer Engineering DRNTU::Engineering::Computer science and engineering We address the problem of body pose tracking in a scenario of multiple camera setup with the aim of recovering body motion robustly and accurately. The tracking is performed on three-dimensional (3D) space using 3D data, including colored volume and 3D optical flow, which are reconstructed at each time step. We introduce strategies to compute multiple camera-based 3D optical flow and have attained efficient and robust 3D motion estimation. Body pose estimation starts with a prediction using 3D optical flow and then is changed to a lower-dimensional global optimization problem. Our method utilizes a voxel subject-specific body model, exploits multiple 3D image cues, and incorporates physical constraints into a stochastic particle-based search initialized from the deterministic prediction and stochastic sampling. It leads to a robust 3D pose tracker. Experiments on publicly available sequences show the robustness and accuracy of our approach. Published version 2013-07-02T03:34:30Z 2019-12-06T13:36:01Z 2013-07-02T03:34:30Z 2019-12-06T13:36:01Z 2012 2012 Journal Article Zhang, Z., & Seah, H. S. (2012). Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction. Applied Optics, 51(23), 5686-5697. https://hdl.handle.net/10356/79884 http://hdl.handle.net/10220/10888 10.1364/AO.51.005686 en Applied optics © 2012 Optical Society of America. This paper was published in Applied Optics and is made available as an electronic reprint (preprint) with permission of Optical Society of America. The paper can be found at the following official DOI: [http://dx.doi.org/10.1364/AO.51.005686]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf |
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DRNTU::Engineering::Computer science and engineering Zheng, Zhang Seah, Hock Soon Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
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We address the problem of body pose tracking in a scenario of multiple camera setup with the aim of recovering body motion robustly and accurately. The tracking is performed on three-dimensional (3D) space using 3D data, including colored volume and 3D optical flow, which are reconstructed at each time step. We introduce strategies to compute multiple camera-based 3D optical flow and have attained efficient and robust 3D motion estimation. Body pose estimation starts with a prediction using 3D optical flow and then is changed to a lower-dimensional global optimization problem. Our method utilizes a voxel subject-specific body model, exploits multiple 3D image cues, and incorporates physical constraints into a stochastic particle-based search initialized from the deterministic prediction and stochastic sampling. It leads to a robust 3D pose tracker. Experiments on publicly available sequences show the robustness and accuracy of our approach. |
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School of Computer Engineering |
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School of Computer Engineering Zheng, Zhang Seah, Hock Soon |
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Article |
author |
Zheng, Zhang Seah, Hock Soon |
author_sort |
Zheng, Zhang |
title |
Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
title_short |
Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
title_full |
Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
title_fullStr |
Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
title_full_unstemmed |
Skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
title_sort |
skeleton body pose tracking from efficient three-dimensional motion estimation and volumetric reconstruction |
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2013 |
url |
https://hdl.handle.net/10356/79884 http://hdl.handle.net/10220/10888 |
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1681059339735924736 |