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A novel method for detecting lips , eyes and faces in real time. Real-Time Imaging (2003) 277–287 Cheng-Chin Chiang*,Wen-Kai Tai,Mau-Tsuen Yang, Yi-Ting Huang,Chi-Jaung Huang Department of Computer Science and Information Engineering, National Dong Hwa University 報告者 何寬宸.
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A novel method for detecting lips , eyes and faces in real time Real-Time Imaging (2003) 277–287 Cheng-Chin Chiang*,Wen-Kai Tai,Mau-Tsuen Yang, Yi-Ting Huang,Chi-Jaung Huang Department of Computer Science and Information Engineering, National Dong Hwa University 報告者 何寬宸
Real-time face detection algorithm • Real-time face detection • locating faces in images and videos • finds not only the face regions • precise locations of the facial components (eyes and lips) • Simple quadratic polynomial model • skin pixels • lips • Removes the falsely extracted components • verifying with rules derived from the spatial and geometrical relationships of facial components. • Experimental results • both accuracy and speed for detecting faces
Rules for skin-color region extraction 1/3 • The purpose • reduce the searching time for possible face regions • Alleviate the influence of environment light brightness • adopts the chromatic color coordinate for color representation
Rules for skin-color region extraction 3/3 • Filter out the non-skin
Rules for lips and eyes detection • Higher extraction speed • The discrimination function should be computationally efficient • The detection of lip pixels can be done in parallel with the detection of skin pixels in one scan of the image or video frame. • Eye components are extracted • histogram-equalized grayscale image • threshold operation (Threshold =20)
Rules for component verifications and face region determination • Angle • be in the range [-45 45] • Spatial rules • Geometry rules
The arbitration of confusing eye–lip triangles • Skin color ratio (SCR)
Performance evaluation • The implemented system has two modes of operations. • detect faces in video frames captured from a PC camera in real time. • off-line mode that is designed to detect faces in still images. • Among these 1000 images • 815 images with the dimension of 320 X240 • 185 images from WWW.
Concluding remarks • The light condition must be normal. • light compensation/correction pre-processing • The facial components must appear on the images as clearly as possible • developing more improved component-based detection • verification process for incomplete facial components.
Vision and Autonomous • Systems Center (VSAC) of CMU,on the web page • http://vasc.ri.cmu.edu/cgi-bin/demos/findface.cgi.