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ISRN Machine Vision
Volume 2012 (2012), Article ID 235396, 11 pages
Research Article

3D Human Motion Tracking and Reconstruction Using DCT Matrix Descriptor

Electrical Engineering Department, Faculty of Engineering, Shahed University, Tehran 33191-18651, Iran

Received 30 January 2012; Accepted 19 February 2012

Academic Editors: C.-C. Han and J. Heikkilä

Copyright © 2012 Alireza Behrad and Nadia Roodsarabi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One of the most important issues in human motion analysis is the tracking and 3D reconstruction of human motion, which utilizes the anatomic points' positions. These points can uniquely define the position and orientation of all anatomical segments. In this work, a new method is proposed for tracking and 3D reconstruction of human motion from the image sequence of a monocular static camera. In this method, 2D tracking is used for 3D reconstruction, which a database of selected frames is used for the correction of tracking process. The method utilizes a new image descriptor based on discrete cosine transform (DCT), which is employed in different stages of the algorithm. The advantage of using this descriptor is the capabilities of selecting proper frequency regions in various tasks, which results in an efficient tracking and pose matching algorithms. The tracking and matching algorithms are based on reference descriptor matrixes (RDMs), which are updated after each stage based on the frequency regions in DCT blocks. Finally, 3D reconstruction is performed using Taylor’s method. Experimental results show the promise of the algorithm.