DocumentCode
2208145
Title
Exploiting automatic image segmentation to human detection and depth estimation
Author
Tseng, Hsiao-Chun ; Shyu, Jia-Jye ; Chang, Jyh-Yeong ; Lin, Chin-Teng
Author_Institution
Dept. of Electr. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fYear
2011
fDate
11-15 April 2011
Firstpage
19
Lastpage
25
Abstract
In this paper, we combine image segmentation techniques and face detection methods to extract the human from scenes. Firstly, skin regions are detected and an ellipse fitting method is employed to detect the face region and consequently locate the human position. Then we propose an improved automatic seeded region growing algorithm to segment the image. The initial seeds are generated automatically, and the remaining pixels are classified to the nearest region. After the region growing procedure, two neighboring regions with high similarity are merged. The human body is determined by confining semantic human body region in segmented regions, and those belonging to the human face and human body are merged afterward. Lastly, we will detect the human vertical y-coordinate values in the image, and the depths can then be estimated according to the depth look-up tables of the camera.
Keywords
face recognition; feature extraction; image segmentation; object detection; table lookup; automatic image segmentation techniques; automatic seeded region growing algorithm; depth estimation; depth look-up tables; ellipse fitting method; face detection methods; human detection; skin region detection; vertical y-coordinate values; Cameras; Estimation; Image segmentation; Pixel; Human Depth Estimation; Human Detection; Region Growing; Skin Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP), 2011 IEEE Symposium on
Conference_Location
Paris
Print_ISBN
978-1-4244-9913-7
Type
conf
DOI
10.1109/CIMSIVP.2011.5949245
Filename
5949245
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