Fast Gender Recognition by Using a Shared-Integral-Image Approach
學年 97
學期 2
發表日期 2009-04-19
作品名稱 Fast Gender Recognition by Using a Shared-Integral-Image Approach
作品名稱(其他語言)
著者 Shen, Bau-cheng; Chen, Chu-song; Hsu, Hui-huang
作品所屬單位 淡江大學資訊工程學系
出版者 IEEE Computer Society
會議名稱 Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
會議地點 Taipei, Taiwan
摘要 We develop a new approach for gender recognition. In this paper, our approach uses the rectangle feature vector (RFV) as a representation to identify humans' gender from their faces. The RFV is computationally fast and effective to encode intensity variations of local regions of human face. By only using few rectangle features learned by AdaBoost, we present a gender identifier. We then use nonlinear support vector machines for classification, and obtain more accurate identification results.
關鍵字 AdaBoost;Gender Recognition;Integral Image;Real AdaBoost;Support Vector Machine
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20090419~20090424
通訊作者
國別 TWN
公開徵稿 Y
出版型式
出處 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009), pp.521-524
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