Human segmentation on sports simulator using hierarchical template mathcing

This paper presents human segmentation using parts of human body shape, which is for recognizing human pose on sports simulator. It is very difficult to segment human body in unsettled environment which includes various clothes style, illumination or the shape of human body. Principle feature points...

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Bibliographic Details
Published in2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) pp. 677 - 680
Main Authors Minjong Kim, Suyoung Chi, Youngsook Jeong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2014
Subjects
Elbow
Foot
Head
hierarchical template matching
Hip
horse-riding simulator
human segmentation
Image segmentation
Knee
part shape analysis
Shape
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Summary:This paper presents human segmentation using parts of human body shape, which is for recognizing human pose on sports simulator. It is very difficult to segment human body in unsettled environment which includes various clothes style, illumination or the shape of human body. Principle feature points are extracted in seven parts of the human body: head, shoulder, elbow, hand, hip, knee, and foot. Five parts of human body such as head, hand, hip, knee and foot segmented using hierarchical template matching and shape average image. The other parts of human body segmented using shadow edge and geometric information because shoulder and elbow boundary lines are ambiguous so these inner parts need to delicate processing. To evaluate proposed algorithm, 200 pose images for 5 human on ETRI database have used and we have acquired an encouraging experimental result of 85 percent on average.
DOI:10.1109/URAI.2014.7057495