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Proceedings Paper

Learning and fusing multiple cues for indoor video segmentation
Author(s): Chunlei Shi; Wenjia Yang; Zhi Chai
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Paper Abstract

This paper presents an algorithm for the automatic segmentation of indoor videos into foreground and background layers. Segmenting foreground from an indoor video with local foreground motion and illumination changes is challenging. We first detect key frames with reliable motion using nonparametric model in chromaticity space. From these key frames, we learn an appearance model as a color degenerating model. Robust indoor video segmentation is achieved by combining these learned color and structure cues in a Markov random field framework. Experimental results on different sequences demonstrate the effectiveness of our algorithm.

Paper Details

Date Published: 27 October 2013
PDF: 5 pages
Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190Q (27 October 2013); doi: 10.1117/12.2030714
Show Author Affiliations
Chunlei Shi, Beijing Instititute of Environmental Features (China)
Science and Technology on Optical Radiation Lab. (China)
Wenjia Yang, Beijing Instititute of Environmental Features (China)
Science and Technology on Optical Radiation Lab. (China)
Zhi Chai, Beijing Instititute of Environmental Features (China)
Science and Technology on Optical Radiation Lab. (China)


Published in SPIE Proceedings Vol. 8919:
MIPPR 2013: Pattern Recognition and Computer Vision
Zhiguo Cao, Editor(s)

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