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Title: Articulated motion reconstruction from feature points
Authors: Li, Baihua
Meng, Qinggang
Holstein, Horst
Keywords: Non-rigid articulated motion
Point pattern matching
Non-rigid pose estimation
Motion tracking and object recognition
Issue Date: 2008
Publisher: © Pattern Recognition Society. Published by Elsevier Ltd.
Citation: LI, B., MENG, Q. and HOLSTEIN, H., 2008. Articulated motion reconstruction from feature points. Pattern Recognition, 41 (1), pp. 418 - 431.
Abstract: A fundamental task of reconstructing non-rigid articulated motion from sequences of unstructured feature points is to solve the problem of feature correspondence and motion estimation. This problem is challenging in high-dimensional configuration spaces. In this paper, we propose a general model-based dynamic point matching algorithm to reconstruct freeform non-rigid articulated movements from data presented solely by sparse feature points. The algorithm integrates key-frame-based self-initialising hierarchial segmental matching with inter-frame tracking to achieve computation effectiveness and robustness in the presence of data noise. A dynamic scheme of motion verification, dynamic key-frame-shift identification and backward parent-segment correction, incorporating temporal coherency embedded in inter-frames, is employed to enhance the segment-based spatial matching. Such a spatial–temporal approach ultimately reduces the ambiguity of identification inherent in a single frame. Performance evaluation is provided by a series of empirical analyses using synthetic data. Testing on motion capture data for a common articulated motion, namely human motion, gave feature-point identification and matching without the need for manual intervention, in buffered real-time. These results demonstrate the proposed algorithm to be a candidate for feature-based real-time reconstruction tasks involving self-resuming tracking for articulated motion.
Description: Closed access. This article was published in the journal, Pattern Recognition [© Pattern Recognition Society. Published by Elsevier Ltd.] and the definitive version is available at: http://dx.doi.org/10.1016/j.patcog.2007.06.002
Version: Published
DOI: 10.1016/j.patcog.2007.06.002
URI: https://dspace.lboro.ac.uk/2134/14645
Publisher Link: http://dx.doi.org/10.1016/j.patcog.2007.06.002
ISSN: 0031-3203
Appears in Collections:Closed Access (Computer Science)

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