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
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;
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
DOI :
10.1109/CIMSIVP.2011.5949245