Human object segmentation using Gaussian mixture model and graph cuts

Abstract

In this paper, we propose an efficient approach to automatic human object segmentation. First, foreground (human object) model and background model are built based on the face detection result, and are used to obtain the seed pixels for foreground and background, respectively. Then seed pixels are clustered using K-means algorithm, and Gaussian mixture… (More)

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@article{Ding2010HumanOS, title={Human object segmentation using Gaussian mixture model and graph cuts}, author={Baoyan Ding and Ran Shi and Zhi Liu and Zhaoyang Zhang}, journal={2010 International Conference on Audio, Language and Image Processing}, year={2010}, pages={787-790} }