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Real Time Face Detection from Color Video Stream Based on PCA Method
Washington, DC October 15-October 17
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AIPR.2003.128426332nd Applied Imagery Pattern Recognit ...
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Rajkiran Gottumukkal, Old Dominion University, Norfolk, VA
Vijayan K. Asari, Old Dominion University, Norfolk, VA
We present a face detection system capable of detection of faces in real time from a streaming color video. Currently this system is able to detect faces as long as both the eyes are visible in the image plane. Extracting skin color regions from a color image is the first step in this system. Skin color detection is used to segment regions of the image that correspond to face regions based on pixel color. Under normal illumination conditions, skin color takes small regions of the color space. By using this information, we can classify each pixel of the image as skin region or non-skin region. By scanning the skin regions, regions that do not have shape of a face are removed. Principle Component Analysis (PCA) is used to classify if a particular skin region is a face or a non-face. The PCA algorithm is trained for frontal view faces only. The system is tested with images captured by a surveillance camera in real time.
Citation:
Rajkiran Gottumukkal, Vijayan K. Asari, "Real Time Face Detection from Color Video Stream Based on PCA Method," aipr, pp.146, 32nd Applied Imagery Pattern Recognition Workshop (AIPR'03), 2003
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