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吳家宇 吳明翰 Face Detection Based on Template Matching and 2DPCA Algorithm 2009/01/14
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IntroductionIntroduction Face recognition Face detection Feature extraction Feature matching Related Methods Skin-based detection method Neural networks method SVM In this paper Template matching algorithm 2DPCA algorithm
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Face Detection
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First step Preprocess the image Normalize Histogram equalization Luminance compensation Second step Search rectangle regions Last step Detect every detection window hierarchically Face Detection Algorithm
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FlowchartFlowchart
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Resize the image – Resized into 400*300 pixel Histogram equalize the image Pre-ProcessingPre-Processing
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Two-eye template Choose 30 standard face images and cut out a pair of eyes regions Get a 20*10 pixel two-eye template via calculating average number to many couples of eyes regions Face template Enlarged nearby based on the eyes template and construct 20*25 pixel face template Most non-face image blocks which interrelated coefficient is less than value T are discarded Template Matching Two-eye templateFace template Denotes separately a gray matrix average value Standard deviation
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PCA – Matrices-to-vector conversion High dimensional vector space Difficult to evaluate covariance matrix Time-consuming 2DPCA – Directly computes eigenvectors of image covariance matrix – More efficiently than PCA – Easier to evaluate covariance matrix – Less time to determine the corresponding eigenvectors Comparison between PCA and 2DPCA
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2DPCA2DPCA
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2DPCA2DPCA
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Minimal distance classifier – Realizes classification to every image matrix – Let – The detection windows corresponding to B are taken account of face region – Otherwise the detection windows are non-face Classification-Merging After two hierarchical detection – Most faces may be detected at multiple nearby positions or scales – Overlapping detected windows should be merged Merging
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ComparisonComparison
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ResultResult
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ResultResult
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Training Data Bao Face Database – Lots of face images, mostly people from Asia. Single face pictures are in the "one faces" subdirectory.
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DemoDemo
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DemoDemo
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