Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/116104
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Type: Conference paper
Title: A relaxation method to articulated trajectory reconstruction from monocular image sequence
Author: Li, B.
Dai, Y.
He, M.
Van Den Hengel, A.
Citation: Proceedings: 2014 IEEE China Summit & International Conference on Signal and Information Processing, 2014, pp.389-393
Publisher: IEEE
Issue Date: 2014
ISBN: 9781479954032
Conference Name: 2nd IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP 2014) (9 Jul 2014 - 13 Jul 2014 : Xi'an, China)
Statement of
Responsibility: 
Bo Li, Yuchao Dai, Mingyi He, Anton van den Hengel
Abstract: In this paper, we present a novel method for articulated trajectory reconstruction from a monocular image sequence. We propose a relaxation-based objective function, which utilises both smoothness and geometric constraints, posing articulated trajectory reconstruction as a non-linear optimization problem. The main advantage of this approach is that it remains the re-constructive power of the original algorithm, while improving its robustness to the inevitable noise in the data. Furthermore, we present an effective approach to estimating the parameters of our objective function. Experimental results on the CMU motion capture dataset show that our proposed algorithm is effective.
Keywords: articulated trajectory
noise
relaxation
robust
smoothness
Rights: © 2014 IEEE
DOI: 10.1109/ChinaSIP.2014.6889270
Grant ID: http://purl.org/au-research/grants/arc/DE140100180
Appears in Collections:Aurora harvest 3
Australian Institute for Machine Learning publications

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