Multi-person close-up real-time recognition and automatic screenshot method for large live broadcasting scene

Abstract

The invention discloses a multi-person close-up real-time recognition and automatic screenshot method for a large live broadcasting scene. The method particularly comprises steps: a face size, definition and a face position are used as first, second and third indexes for a screenshot; firstly, the current video frame image of a live broadcasting video is acquired in real time, a face in the videoframe image is detected, and a face area is acquired and tracked; and then, the face size, the definition and the position in the face area are evaluated sequentially, a face image meeting a screenshot standard is further selected, the current video frame image screenshot is saved and sent to a face recognition model for recognition, and a recognition result is outputted. The method can be appliedto a large live broadcasting scene to carry out recognition and screenshot on multiple person close-ups in the video, automatic screenshot for saving is carried out when a screenshot index is met, and a screenshot with a better quality is ensured to be acquired.

Description

Technical field: [0001] The invention relates to a multi-person close-up real-time recognition and automatic screenshot method for large-scale live broadcast scenes, and belongs to the technical field of video image processing technology. Background technique: [0002] On various live broadcast platforms, such as regular conference live broadcasts, football live broadcasts, or large-scale party live broadcasts, it is necessary to take screenshots under certain circumstances and perform face recognition on the characters on the pictures, so as to facilitate graphic introduction. People must be detected if screenshots are needed. The key technology is face detection, and traditional face detection is usually detected in real time, so a large number of repeated different face snapshots of the same object will be generated during the detection process, and the quality In addition, if all snapshots are saved for face recognition, it will bring the disadvantages of large storage c...

AI Technical Summary

Problems solved by technology

People must be detected if screenshots are needed. The key technology is face detection, and traditional face detection is usually detected in real time, so a large number of repeated different face snapshots of the same object will be generated during the detection process, and the quality In addition, if all snapshots are saved for face recognition, it will bring the disadvantages of large storage capacity and poor face recognition effect. Therefore, in order to solve this problem, the present invention proposes an image quality evaluation method, which can only satisfy Screenshots are required to save and identify

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