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Patch-wise skin segmentation of human body parts via deep neural networks
Tao Xu; Zhaoxiang Zhang; Yunhong Wang
2015-08-10
发表期刊Journal of Electronic Imaging
卷号24期号:4页码:1-13
摘要In human-centric technologies, skin segmentation of body parts is a prerequisite for high-level processing. The traditional method of skin detection is pixel-wise detection coupled with morphological operations. Pixel-wise methods usually generate a number of false samples and outlier skin pixels, which can make it difficult for morphological operations to provide satisfactory results in complex scenarios. Furthermore, in many cases only a coarse region is required (e.g., the bounding-box of the face) rather than detailed pixel-wise labeling. A patch-wise skin segmentation method is proposed based on deep neural networks. Our method treats image patches as processing units instead of pixels, which directly exploits the spatial information of pixels in the detection stage rather than using morphological operations on isolated pixels after detection. An image patch dataset is built and deep skin models (DSMs) are trained based on the new dataset. Trained DSMs are then integrated into a sliding window framework to segment skin regions of the human body parts. Experiments on standard benchmarks demonstrate that DSMs provide more explicit skin region of interest candidates than pixel-wise methods in complex scenarios, and achieve competitive performance on pixel-wise skin detection.
关键词Image Segmentation Skin
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13213
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
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GB/T 7714
Tao Xu,Zhaoxiang Zhang,Yunhong Wang. Patch-wise skin segmentation of human body parts via deep neural networks[J]. Journal of Electronic Imaging,2015,24(4):1-13.
APA Tao Xu,Zhaoxiang Zhang,&Yunhong Wang.(2015).Patch-wise skin segmentation of human body parts via deep neural networks.Journal of Electronic Imaging,24(4),1-13.
MLA Tao Xu,et al."Patch-wise skin segmentation of human body parts via deep neural networks".Journal of Electronic Imaging 24.4(2015):1-13.
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