Human Face Extraction and Recognition Using Radial Basis Function Networks
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概要
- 論文の詳細を見る
Partial face images, e.g., eyes, nose, and ear images are significant for face recognition. In this paper, we present a method for partial face extraction and recognition based on Radial Basis Function (RBF) networks. Focus has been centered on using ear images because they are not influenced by facial expression, and the influences of aging are negligible. Original human side face image with 320 × 240 pixels is input, and then the RBF network locates the ear and extracts it with a 200 × 120 pixel image. Next, another RBF network is constructed for the purpose of recognition. An algorithm that determines the radius of an RBF function is proposed. Dynamic radius, so called as compared to static one, is found through the algorithm that makes RBF functions adaptable to the training samples. We built a database that contains 600 side face images, from 100 people, to test the method and the results of both extraction and recognition ar satisfied.
- 社団法人電子情報通信学会の論文
- 2003-05-01
著者
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Takahashi Yukitoshi
Department of Pediatrics, Gifu University School of Medicine
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Sato Kiminori
Department Of Neurosurgery Nihon University School Of Medicine
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Takahashi Yukitoshi
Department Of Information And Computer Science Kagoshima University
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HE Nan
Department of Chemistry, Fudan University
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He Nan
Department Of Computer Science University Of Nebraska
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He Nan
Department Of Chemistry Fudan University
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Sato Kiminori
Department Of Electrical Communication Faculty Of Engineering Tohoku University
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Sato Kiminori
Department Of Information And Computer Science Kagoshima University
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Takahashi Yukitoshi
Department of Clinical Research, National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders
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