期刊論文
| 學年 | 97 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2009-05-01 |
| 作品名稱 | Gender Recognition from Human Faces by Using a Shared-Integral-Image Approach |
| 作品名稱（其他語言） | |
| 著者 | Shen, Bao-cheng; Hsu, Hui-huang; Chen, Chu-song |
| 單位 | 淡江大學資訊工程學系 |
| 出版者 | Allahabad: Pushpa Publishing House |
| 著錄名稱、卷期、頁數 | Far East Journal of Experimental and Theoretical Artificial Intelligence 3(2), pp.101-112 |
| 摘要 | We develop an approach for gender recognition based on human faces. We combine rectangle features extracted from the human-face region into a rectangle-feature vector (RFV). The RFV is computationally fast and effective in encoding intensity variations of local regions of human face. By only using few rectangle features learned by AdaBoost, we present an effective gender identification approach. We then use nonlinear support vector machines for classification, and obtain more accurate recognition results. Experimental results show that our approach performs well for the Feret database. |
| 關鍵字 | Gender Recognition; AdaBoost; Real Ad-aBoost; Support Vector Machine; Integral Image |
| 語言 | en |
| ISSN | 0974-3261 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | |
| 國別 | IND |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59920 ) |