Compressed domain statistical snake segmentation for real-time tracking of objects in airborne videos

Shuqun Zhang; Mo Chen

doi:10.1117/12.735232

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24 September 2007 Compressed domain statistical snake segmentation for real-time tracking of objects in airborne videos

Shuqun Zhang, Mo Chen

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Proceedings Volume 6696, Applications of Digital Image Processing XXX; 669624 (2007) https://doi.org/10.1117/12.735232
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

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.

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Shuqun Zhang and Mo Chen "Compressed domain statistical snake segmentation for real-time tracking of objects in airborne videos", Proc. SPIE 6696, Applications of Digital Image Processing XXX, 669624 (24 September 2007); https://doi.org/10.1117/12.735232

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