Three-dimensional face age classifying device and method based on three-dimensional point cloud

Abstract

The invention discloses a three-dimensional face age classifying device and method based on three-dimensional point cloud. The device comprises a characteristic region detection unit for positioning a characteristic region of the three-dimensional point cloud, a mapping unit for mapping the three-dimensional point cloud into depth image space, a characteristic calculating unit for calculating the depth image presentation characteristics of a mapped depth image and an age classifier calculating unit for carrying out age classifying based on the depth image presentation characteristic. The method includes the steps of detecting the characteristic region, mapping the depth image, calculating the image presentation characteristic, and carrying out classifying. According to the device and method, the mode that an image presentation characteristic pool is built in cooperation with a plurality of textural characteristics is used, the characteristics of a three-dimensional depth face image are accurately described, then accurate classifying is achieved through an age random forest classifier on the basis of an image presentation characteristic set, and the classifying accuracy is high.

Description

technical field [0001] The present invention relates to the technical field of three-dimensional face recognition, in particular to a three-dimensional face age classification device and method based on three-dimensional point clouds. Background technique [0002] Compared with 2D face recognition, 3D face recognition has the advantages of being robust to illumination and less affected by factors such as posture and expression. Therefore, after the rapid development of 3D data acquisition technology and the great improvement in the quality and accuracy of 3D data, Many scholars devote their research to this field. [0003] CN20101025690 proposes the relevant features of three-dimensional bending invariant to describe the characteristics of human face. This method extracts the relevant features of the bending invariant by encoding the local features of the bending invariant of adjacent nodes on the surface of the three-dimensional face; signs the relevant features of the ben...

AI Technical Summary

Problems solved by technology

However, due to the complex calculation required to extract variable-related features, the further application of this method is limited in terms of efficiency;

Images