Local descriptor-based three-dimensional face recognition method

Abstract

The invention discloses a local descriptor-based three-dimensional face recognition method, which comprises the following steps of: (1) preprocessing a face library model and a testing face model by face cutting, gesture normalization and dilution, and finally establishing a face principle axis coordinate system by taking the tip of nose as a center; (2) extracting equidistant contour lines from the face library model and the testing face model, extracting sixteen contour lines equidistant to a point of the tip of nose by taking the point of tip of nose as a center, and resampling to acquire the same number of sampling points; (3) latticing the face library model and the testing face model, and extracting a local projection area on the acquired sampling points in the step (3) as a local characteristic; (4) establishing one-to-one correspondence between the sampling points in the same sequence on the face library model and the testing face model, and comparing local characteristics of corresponding points; and (5) taking Euclidean distance of the local characteristics between the corresponding points as similarity, and selecting a face which is most similar to the testing face from the face library as a recognition result.

Description

technical field [0001] The invention relates to a three-dimensional face recognition method based on local descriptors. For any sampling point, three neighborhood point sets are adaptively selected, and the projected areas projected on the three planes XOY, YOZ and XOZ in turn are taken as the The local features of points, using such a local descriptor for face recognition, has a good face representation effect, and reduces the impact of expression on recognition. Background technique [0002] Biometric identification has important applications in the field of security, especially compared with fingerprints, irises and other features, automatic face recognition technology has attracted more and more attention due to its advantages of non-contact, high acceptability, and good concealment. , has huge room for development. [0003] The traditional face recognition technology based on two-dimensional photos is greatly affected by factors such as lighting, posture, and makeup. ...

AI Technical Summary

Problems solved by technology

However, the amount of 3D face data is large, there are many interference areas, and the amount of calculation is large, and the non-rigid deformation of the face surface due to expressions affects the performance of 3D face recognition based on geometric information.

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