會議論文
| 學年 | 97 |
|---|---|
| 學期 | 1 |
| 發表日期 | 2008-11-21 |
| 作品名稱 | A Shared-Integral-Image Approach for Fast Gender Recognition |
| 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 | 臺北縣淡水鎮 : 淡江大學 |
| 會議名稱 | 第十三屆人工智慧與應用研討會=The 13th conference on artificial intelligence and applications |
| 會議地點 | 宜蘭縣, 臺灣 |
| 摘要 | In this paper, we develop a new approach for gender recognition. 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 an effective gender identifier. We then use nonlinear support vector machines for classification, and obtain more accurate identification results. Experimental results show that our approach performs well for the Feret database. |
| 關鍵字 | Gender Recognition;AdaBoost, Real AdaBoost;Support Vector Machine;Integral Image |
| 語言 | en |
| 收錄於 | |
| 會議性質 | 國內 |
| 校內研討會地點 | 蘭陽校園 |
| 研討會時間 | 20081121~20081122 |
| 通訊作者 | |
| 國別 | TWN |
| 公開徵稿 | Y |
| 出版型式 | 紙本 |
| 出處 | 第十三屆人工智慧與應用研討會論文集=The 13th conference on artificial intelligence and applications, pp.13-17 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98197 ) |