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Proceedings Paper

Target detection from MPEG video based on low-rank filtering in the compressed domain
Author(s): Teeradache Viangteeravat; Soradech Krootjohn; D. Mitchell Wilkes
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Paper Abstract

There are advantages of using the motion vector obtained from the MPEG video coding to perform target of interest identification in the field. In practice, however, environment noise, time-varying, and uncertainty factors affect their performance reliably and accurately detecting targets of interest. In this paper, we proposed a novel low rank filtering based on L1 norm in order to straighten up single rogue or outliers that might show up fairly often. Finally, a simple average smoothing filter was applied to reduce vector quantization noise. By using the low rank filtering based on L1 norm, the dominant motion vectors from the MPEG video coding can be extracted appropriately with respect to target operational responses and can be used for robust identification of moving target. The performance of the proposed approach was evaluated based on a set of experimental camera motion. The motions, including pan, tilt, and zoom, was computed from the motion vectors, and the residual vectors which are not described by the camera motion are regarded as generated by moving blobs. Events, as a result, can be detected from these moving blobs. It is demonstrated that the approach yields very promising results where motion vectors obtained from the MPEG video coding can be used efficiently to detect and identify moving target in the field.

Paper Details

Date Published: 27 April 2010
PDF: 8 pages
Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 76971J (27 April 2010); doi: 10.1117/12.858032
Show Author Affiliations
Teeradache Viangteeravat, The Univ. of Tennessee Health Science Ctr. (United States)
Soradech Krootjohn, Vanderbilt Univ. (United States)
D. Mitchell Wilkes, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 7697:
Signal Processing, Sensor Fusion, and Target Recognition XIX
Ivan Kadar, Editor(s)

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