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Proceedings Paper

Fast hierarchical knowledge-based approach for human face detection in color images
Author(s): Jun Jiang; Jie Gong; Guilin Zhang; Ruolan Hu
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Paper Abstract

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

Paper Details

Date Published: 21 September 2001
PDF: 9 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441447
Show Author Affiliations
Jun Jiang, Huazhong Univ. of Science and Technology (China)
Jie Gong, Huazhong Univ. of Science and Technology (China)
Guilin Zhang, Huazhong Univ. of Science and Technology (China)
Ruolan Hu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition

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