Super-resolution image restoration method in gait recognition

Abstract

The present invention relates to image fusion and gait recognition of human body, and especially to a super-resolution image restoration method in gait recognition. The present invention provides a super-resolution image restoration method in gait recognition. The image quality of video sequence is increased through the restoration of super-resolution image. The changing interference of background image is greatly reduced thereby reducing the calculation amount in human body detection process. The invention adopts a technical scheme that the prior gait image is degraded to low-resolution gait image in each iteration. The degraded gait image and the error and fuzzy matrix of actual measured low-resolution gait image are used for forming a reverse projection operator for computing the next high-resolution gait image. Namely the high-resolution image (HR image) is obtained by simulating the low-resolution image (LR image) and observing the low-resolution image (LR image) for executing reverse projection. The process is iterated continuously until the time when the error amount reaches least. The super-resolution image restoration method in gait recognition according to the invention is mainly used for personal identification through the gait of human body.

Description

technical field [0001] The invention relates to image fusion and human body gait recognition, in particular to a super-resolution image recovery method in gait recognition. Background technique [0002] Gait recognition is a research field emerging in recent years, which is a combination of biometric recognition and human motion visual analysis. At present, "looking at people" is one of the most active research topics in the field of computer vision. Its core is to use computer vision technology to detect, track, and recognize people from image sequences and understand their behavior. describe. As a part of it, gait recognition has also become a research hotspot, especially in the United Kingdom, the United States and other countries, where a large number of related projects have been carried out. Its application range is very wide, and it can be used in criminal identification, disease detection, and security management. The detection of moving human body is an important ...

AI Technical Summary

Problems solved by technology

Effective segmentation of moving areas is very important for post-processing such as target classification, tracking and recognition. However, due to dynamic changes in background images, such as changes in weather, changes in lighting conditions, background chaos, shadows of moving targets, objects and environments The occlusion between objects or between objects, or even the movement of the camera, etc., make the detection of moving humans a difficult task

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