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Proceedings Paper

Compressed domain statistical snake segmentation for real-time tracking of objects in airborne videos
Author(s): Shuqun Zhang; Mo Chen
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Paper Abstract

We present a new compressed domain method for tracking objects in airborne videos. In the proposed scheme, a statistical snake is used for object segmentation in I-frames, and motion vectors extracted from P-frames are used for tracking the object detected in I-frames. It is shown that the energy function of the statistical snake can be obtained directly from the compressed DCT coefficients without the need of full decompression. The number of snake deformation iterations can be also significantly reduced in compressed domain implementation. The computational cost is significantly reduced by using compressed domain processing while the performance is competitive to that of pixel domain processing. The proposed method is tested using several UAV video sequences, and experiments show that the tracking results are satisfactory.

Paper Details

Date Published: 24 September 2007
PDF: 7 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 669624 (24 September 2007); doi: 10.1117/12.735232
Show Author Affiliations
Shuqun Zhang, College of Staten Island, City Univ. of New York (United States)
Mo Chen, Sate Univ. of New York at Binghamton (United States)


Published in SPIE Proceedings Vol. 6696:
Applications of Digital Image Processing XXX
Andrew G. Tescher, Editor(s)

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