剛性區(qū)域特征點的3維人臉識別
[Abstract]:Aim to solve the problem of facial expression change in 3D face recognition, a 3D facial recognition method based on rigid region feature points is proposed. Methods the feature points of the face image are extracted from the texture image, and the feature points in the non-rigid region are deleted, and then, according to the ordinal number of the sampling points, the feature points of the face image are removed. The 3D geometric information of facial image feature points is obtained from the geometric information of human face space, and the subregions of rigid regions centered on feature points are established. Finally, the sub-regions are used as local features for face recognition testing. The contribution of different sub-regions to face recognition is obtained, and based on the results of face recognition, weighted statistics are carried out. Results the experiment was carried out on the 3D face database of FRGC v2.0. The recognition accuracy of the method was 98.5 and the verification rate was 99.2 when the error acceptance rate (far) was 0.001. This method has good accuracy for 3 D face recognition under non neutral expression. Conclusion this method can effectively overcome the effect of facial expression change on 3D face recognition, and it has good robustness to voids and sharp noises in 3D data, and it is of great significance to improve the performance of 3D face recognition.
【作者單位】: 遼寧工程技術(shù)大學(xué)工商管理學(xué)院;遼寧工程技術(shù)大學(xué)軟件學(xué)院;
【基金】:國家自然科學(xué)基金項目(61172144) 遼寧省科技攻關(guān)計劃項目(2012216026) 遼寧省教育廳科學(xué)研究項目(LJYL-049)~~
【分類號】:TP391.41
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