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ICMI
2000
Springer

Combining Skin Color Model and Neural Network for Rotation Invariant Face Detection

11 years 5 months ago
Combining Skin Color Model and Neural Network for Rotation Invariant Face Detection
Face detection is a key problem in human-computer interaction. In this paper, we present an algorithm for rotation invariant face detection in color images of cluttered scenes. It is a hierarchical approach, which combines a skin color model, a neural network, and an upright face detector. Firstly, the skin color model is used to process the color image to segment the face-like regions from the background. Secondly, the neural network computing and an operation for locating irises are performed to acquire rotation angle of each input window in the face-like regions. Finally, we provide an upright face detector to determine whether or not the rotated window is a face. Those techniques are integrated into a face detection system. The experiments show that the algorithm is robust to different face sizes and various lighting conditions.
Hongming Zhang, Debin Zhao, Wen Gao, Xilin Chen
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where ICMI
Authors Hongming Zhang, Debin Zhao, Wen Gao, Xilin Chen
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