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Proceedings Paper

Automatic video object detection and mask signal removal for efficient video preprocessing
Author(s): Zhihai He
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Paper Abstract

In this work, we consider a generic definition of video object, which is a group of pixels with temporal motion coherence. The generic video object (GVO) is the superset of the conventional video objects discussed in the literature. Because of its motion coherence, the GVO can be easily recognized by the human visual system. However, due to its arbitray spatial distribution, the GVO cannot be easily detected by the existing algorithms which often assume the spatial homogeneousness of the video objects. In this work, we introduce the concept of extended optical flow and develop a dynamic programming framework for the GVO detection. Using this mathematical optimization formulation, whose solution is given by the the Viterbi algorithm, the proposed object detection algorithm is able to discover the motion path of the GVO automatically and refine its spatial location progressively. We apply the GVO detection algorithm to extract and remove the so-called "video mask" signals in the video sequence. Our experimental results show that this type of vision-guided video pre-processing significantly improves the compression efficiency.

Paper Details

Date Published: 18 January 2004
PDF: 9 pages
Proc. SPIE 5308, Visual Communications and Image Processing 2004, (18 January 2004); doi: 10.1117/12.527236
Show Author Affiliations
Zhihai He, Univ. of Missouri/Columbia (United States)


Published in SPIE Proceedings Vol. 5308:
Visual Communications and Image Processing 2004
Sethuraman Panchanathan; Bhaskaran Vasudev, Editor(s)

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