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Spatio-temporal reconstruction for 3D motion recovery

Yang, Jingyu, Guo, Xin, Li, Kun, Wang, Meiyuan, Lai, Yukun ORCID: and Wu, Feng 2020. Spatio-temporal reconstruction for 3D motion recovery. IEEE Transactions on Circuits and Systems for Video Technology 30 (6) , 1583 -1596. 10.1109/TCSVT.2019.2907324

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—This paper addresses the challenge of 3D motion recovery by exploiting the spatio-temporal correlations of corrupted 3D skeleton sequences. We propose a new 3D motion recovery method using spatio-temporal reconstruction, which uses joint low-rank and sparse priors to exploit temporal correlation and an isometric constraint for spatial correlation. The proposed model is formulated as a constrained optimization problem, which is efficiently solved by the augmented Lagrangian method with a Gauss-Newton solver for the subproblem of isometric optimization. Experimental results on the CMU motion capture dataset, Edinburgh dataset and two Kinect datasets demonstrate that the proposed approach achieves better motion recovery than state-of-the-art methods. The proposed method is applicable to Kinect-like skeleton tracking devices and pose estimation methods that cannot provide accurate estimation of complex motions, especially in the presence of occlusion.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 1051-8215
Date of First Compliant Deposit: 22 March 2019
Date of Acceptance: 8 March 2019
Last Modified: 07 Nov 2023 06:32

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