Crime monitoring method based on face recognition technology and behavior and sound recognition

Abstract

The invention provides a crime monitoring method based on the face recognition technology and behavior and sound recognition, which includes the following steps: Step 1, recoding a video through a camera, reducing dimensions of the video to form a picture message ensemble; Step 2, performing the recognition comparison to the picture message ensemble as per an intelligent behavior pattern, and issuing an early warning and storing the video if the comparison is successful; and Step 3, verifying the crime situation by a police on duty, confirming the position of the camera through a GPS for positioning and tracking and confirming the police strength nearby, and sending crime situation to polices nearby by the police on duty, and if no police is on duty, confirming the position of the camera automatically through the GPS for positioning and tracking and confirming the police strength nearby, and sending crime situation to polices nearby and staff on duty. According to the invention, different intelligent behavior patterns are set as per the monitoring requirements of different situations, targeted monitoring is introduced, early warning prevention in advance is realized, the case is prevented from further worsening, the time in solving a criminal case is shortened, and the detection rate is improved.

Description

technical field [0001] The invention relates to a crime monitoring method based on face recognition and behavior voice recognition. Background technique [0002] At present, the face recognition technology is based on the facial features of people. For the input face image or video stream, it is first judged whether there is a face. The location information of facial organs, and then based on this information, further extract the identity features contained in each face, and compare them with known faces to identify the identity of each face; currently face recognition is only based on large Triangular face recognition only completes the recognition of the half part of the face, lacks the recognition of the lower part of the face, the recognition of contour features, and the combination of proportional changes when the shape of the mouth changes; in this way, when the expression changes, the error It is also too large, and the recognition rate is naturally low. [0003] At...

AI Technical Summary

Problems solved by technology

[0002] At present, the face recognition technology is based on the facial features of people. For the input face image or video stream, it is first judged whether there is a face. The location information of facial organs, and then based on this information, further extract the identity features contained in each face, and compare them with known faces to identify the identity of each face; currently face recognition is only based on large Triangular face recognition only completes the recognition of the half part of the face, lacks the recognition of the lower part of the face, the recognition of contour features, and the combination of proportional changes when the shape of the mouth changes; in this way, when the expression changes, the error Also too large, the recognition rate is naturally low

[0003] At the same time, the exis

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