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Forward non-rigid motion tracking for facial MoCap

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Abstract

For the existing motion capture (MoCap) data processing methods, manual interventions are always inevitable, most of which are derived from the data tracking process. This paper addresses the problem of tracking non-rigid 3D facial motions from sequences of raw MoCap data in the presence of noise, outliers and long time missing. We present a novel dynamic spatiotemporal framework to automatically solve the problem. First, based on a 3D facial topological structure, a sophisticated non-rigid motion interpreter (SNRMI) is put forward; together with a dynamic searching scheme, it cannot only track the non-missing data to the maximum extent but recover missing data (it can accurately recover more than five adjacent markers under long time (about 5 seconds) missing) accurately. To rule out wrong tracks of the markers labeled in open structures (such as mouth, eyes), a semantic-based heuristic checking method was raised. Second, since the existing methods have not taken the noise propagation problem into account, a forward processing framework is presented to solve the problem. Another contribution is the proposed method could track facial non-rigid motions automatically and forward, and is believed to greatly reduce even eliminate the requirements of human interventions during the facial MoCap data processing. Experimental results proved the effectiveness, robustness and accuracy of our system.

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Acknowledgements

This work is supported by the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT1109), the Program for Liaoning Science and Technology Research in University (No. LS2010008), the Program for Liaoning Innovative Research Team in University(No. LT2011018), Natural Science Foundation of Liaoning Province (201102008), the Program for Liaoning Key Lab of Intelligent Information Processing and Network Technology in University, “Liaoning BaiQianWan Talents Program (2010921010, 2011921009)” and by the General Project of Basic Research Program of Hunan Provincial Science and Technology Department (Grant No. 2012FJ3034).

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Authors and Affiliations

  1. Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Ministry of Education, Dalian, 116622, China

    Xiaoyong Fang, Xiaopeng Wei, Qiang Zhang & Dongsheng Zhou

  2. School of Computer and Information Science, Hunan Institute of Technology, Hengyang, 421002, China

    Xiaoyong Fang

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  1. Xiaoyong Fang
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Correspondence to Qiang Zhang.

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Fang, X., Wei, X., Zhang, Q. et al. Forward non-rigid motion tracking for facial MoCap. Vis Comput 30, 139–157 (2014). https://doi.org/10.1007/s00371-013-0790-8

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