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3-D motion recovery via low rank matrix restoration on articulation graphs

Li, Kun, Wang, Meiyuan, Lai, Yukun, Yang, Jingyu and Wu, Feng 2017. 3-D motion recovery via low rank matrix restoration on articulation graphs. Presented at: IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, China, 10-14 July 2017. 2017 IEEE International Conference on Multimedia and Expo (ICME). IEEE, pp. 721-726. 10.1109/ICME.2017.8019486

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Abstract

This paper addresses the challenge of 3-D skeleton recovery by exploiting the spatio-temporal correlations of corrupted 3D skeleton sequences. A skeleton sequence is represented as a matrix. We propose a novel low-rank solution that effectively integrates both a low-rank model for robust skeleton recovery based on temporal coherence, and an articulation-graph-based isometric constraint for spatial coherence, namely consistency of bone lengths. 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 and a Kinect dataset show that the proposed approach achieves better recovery accuracy over a state-of-the-art method. The proposed method has wide applicability for skeleton tracking devices, such as the Kinect, because these devices cannot provide accurate reconstructions of complex motions, especially in the presence of occlusion.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
ISBN: 9781509060689
Date of First Compliant Deposit: 16 April 2017
Date of Acceptance: 27 February 2017
Last Modified: 17 May 2018 15:40
URI: http://orca-mwe.cf.ac.uk/id/eprint/99894

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