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Conference Paper Human Segmentation based on GrabCut in Real-Time Video Sequences
Cited 7 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Sohee Park, Jang-Hee Yoo
Issue Date
2014-01
Citation
International Conference on Consumer Electronics (ICCE) 2014, pp.111-112
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICCE.2014.6775931
Abstract
In this paper, we present a fully-automatic human segmentation method without iteration in video sequences. To segment human body accurately, we adopt coarse-to-fine approach using human detection and background subtraction. HoG-based method is used to detect human ROI. Background subtraction is used to subtract subject image in human ROI and skeleton image. The human ROI, the subject image, and the skeleton image are initialization values of GrabCut. The initialization values provide more accurate foreground and background information to GrabCut. Therefore the proposed method can segment human silhouette accurately enough to apply in video analysis without iteration. Experimental results show that the proposed method can be achieved better performance than GrabCut in real-time video sequences. © 2014 IEEE.
KSP Keywords
Background Information, Background Subtraction, Human Body, Human Detection, Human segmentation, Real-time video, Skeleton image, Video sequences, coarse-to-fine, segmentation method, video analysis