文章詳目資料
Journal of Computers EIMEDLINEScopus
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| 篇名 | Image Face Calibration Positioning Based on 3000FPS Algorithm |
|---|---|
| 卷期 | 29:2 |
| 作者 | Xi-bao Wu 、 Chen Jin 、 Xiang-feng Chen 、 Rentian He 、 Ke Lv |
| 頁次 | 055-064 |
| 關鍵字 | 3000FPS 、 face calibration positioning 、 global linear regression 、 random forest trees 、 EI 、 MEDLINE 、 Scopus |
| 出刊日期 | 201804 |
中文摘要
英文摘要
In the face recognition tasks, face pose can have influence on the results of recognition. To improve the accuracy of recognition, we introduced 3000FPS algorithm for face image calibration positioning. Random forests is used to establish each key point, and the output of every tree in random forests, binary feature, is exploited to compose local binary feature, which is used to train a softmax classifier. The experiment show that the recognition accuracy of the algorithm can reach 93.33% on the Helen face dataset, and 94.14% on the LFPW. Meanwhile, multi-face can be aligned and located even though the input image is partially obscured.
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