Method for obtaining a clear face image of a moving human body in a monitored video

Abstract

The invention discloses a method for obtaining a clear face image of a moving human body in a monitored video. Firstly, after a moving human body is detected, an AdaBoost learning algorithm is adopted for detecting the direct human face in a rectangular region which is 1 / 6 of the length of the upper body part; secondly, whether the face area is larger than 10 percent of the whole image area S is judged, if the face area is less than 10 percent of the whole image area S, the face is tracked, and optical parameters of a camera are controlled so that the face area can reach 10 percent of S; if the face area is not less than 10 percent of the whole image area S, whether a definition evaluation function takes a peak value is judged, if the definition evaluation function takes the peak value, the face image is clearest; and finally, the clear face image is saved, and the optical parameters of the camera are controlled so that the camera can be restored to a normal field monitoring status. The invention realizes feature emphasis of the face, is easy to carry out and can obtain the clear face image from the monitored video with low resolution in the case of long distance.

Description

technical field [0001] The present invention relates to the field of video monitoring, more precisely, the present invention relates to large-scale monitoring of security-sensitive occasions such as banks, supermarkets, hospitals, prisons, garages, airports, government departments, and access control. Background technique [0002] In video surveillance, face detection and tracking technology has become the most ideal basis for identity verification and the most concerned technology due to its advantages of concealed operation, non-contact information collection, directness, and no need for human cooperation. At present, there are many researches on face detection and tracking abroad, such as MIT, CMU, etc.; domestic Tsinghua University, Beijing University of Technology, Institute of Computing Technology, Chinese Academy of Sciences, and Institute of Automation, Chinese Academy of Sciences all have personnel engaged in human face detection and tracking. Research related to fa...

AI Technical Summary

Problems solved by technology

Due to the limited shooting range and accuracy of the camera, if the target moves out of the visible range or the monitoring target is far away from the installation position of the camera, the system will lose accurate capture of the target. The face information of the person cannot be clearly recorded. Even if the video image obtained from the recording is enlarged afterwards, the face image is still unclear due to the low resolution, which is not conducive to future verification work

Images