Method for collecting and optimizing face image sample based on heterogeneous active visual network

Abstract

The invention discloses a method for collecting and optimizing a face image sample based on a heterogeneous active visual network, wherein the optimizing process is as follows: in every Delta t time, all cameras are performed target distribution and state regulation to finish one round of target image sample collection; the process of optimizing variables in sequence is as follows: according to distribution relationship between the camera and the target, position and facing angle of the camera in a world coordinate system, and focal distance of the camera, maximizing total experience evaluation function of all targets as the optimization target and traversing target distribution plans; under each target distribution plan, adopting the genetic algorithm, solving optimization variables to enable the target evaluation function to be the maximum; selecting the best distribution plan so as to obtain the maximum total experience evaluation function. The method improves the resolution ratio and the attitude angle of the face in the image by the active visual technology, optimizes the sample collection process by the heterogeneous active visual network, obtains face image sample with good resolution ratio and rich attitude angles in order to register and identify face.

Description

technical field [0001] The invention belongs to the technical field of face recognition, in particular to a face image sample acquisition and optimization method based on a heterogeneous active vision network. Background technique [0002] Face recognition technology has good application value and application prospects in both civilian and military fields, mainly including face image sample collection, sample image preprocessing, classifier training (also known as face registration) and sample recognition (also known as human face recognition). Face recognition) These technical links, currently there are few studies on the sample collection link. [0003] In the application scenario of human-computer interaction, there are already some studies on the sample collection link. These technologies and research usually use the rotation and zoom of the camera installed on the robot, as well as the movement of the robot itself, to collect face image samples with appropriate resolut...

AI Technical Summary

Problems solved by technology

At this time, the resolution of the collected face image samples is often not high enough; the attitude angle is not positive enough, or the different attitude angles are not rich

Such face image samples are not effective in face registration and recognition

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