Learning and fusing multiple cues for indoor video segmentation

Chunlei Shi; Wenjia Yang; Zhi Chai

doi:10.1117/12.2030714

27 October 2013 Learning and fusing multiple cues for indoor video segmentation

Chunlei Shi, Wenjia Yang, Zhi Chai

Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190Q (2013) https://doi.org/10.1117/12.2030714
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

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.

Citation Download Citation

Chunlei Shi, Wenjia Yang, and Zhi Chai "Learning and fusing multiple cues for indoor video segmentation", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190Q (27 October 2013); https://doi.org/10.1117/12.2030714

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