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Proceedings Paper

Voting based object boundary reconstruction
Author(s): Qi Tian; Like Zhang; Jingsheng Ma
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Paper Abstract

A voting-based object boundary reconstruction approach is proposed in this paper. Morphological technique was adopted in many applications for video object extraction to reconstruct the missing pixels. However, when the missing areas become large, the morphological processing cannot bring us good results. Recently, Tensor voting has attracted people's attention, and it can be used for boundary estimation on curves or irregular trajectories. However, the complexity of saliency tensor creation limits its applications in real-time systems. An alternative approach based on tensor voting is introduced in this paper. Rather than creating saliency tensors, we use a "2-pass" method for orientation estimation. For the first pass, Sobel d*etector is applied on a coarse boundary image to get the gradient map. In the second pass, each pixel puts decreasing weights based on its gradient information, and the direction with maximum weights sum is selected as the correct orientation of the pixel. After the orientation map is obtained, pixels begin linking edges or intersections along their direction. The approach is applied to various video surveillance clips under different conditions, and the experimental results demonstrate significant improvement on the final extracted objects accuracy.

Paper Details

Date Published: 24 June 2005
PDF: 9 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59606B (24 June 2005); doi: 10.1117/12.633444
Show Author Affiliations
Qi Tian, Univ. of Texas at San Antonio (United States)
Like Zhang, Univ. of Texas at San Antonio (United States)
Jingsheng Ma, Heriot-Watt Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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