Facial expression analysis system for people in gathering scene

Abstract

The invention discloses a facial expression analysis system for people in a gathering scene. The system comprises a first camera, a second camera, a semicircular sliding rail and a host, wherein the first camera and the second camera are installed at the two ends of the semi-circular sliding rail, and the camera shooting direction of the first camera and the second camera is perpendicular to the tangent line of the semi-circular sliding rail at the cameras. The first camera and the second camera move in front of the measured point in a semi-circular manner along the semi-circular slide rail soas to ensure that a fixed angle is formed between the first camera and the measured point; the semicircular slide rail is mounted on the stage in front of the auditorium; the host comprises a pre-designed analysis algorithm, photos shot by the first camera and the second camera are transmitted to the host for analysis through a local area network, and an analysis result is transmitted to the cloud through the Internet after the host finishes analysis. According to face rotation angle information acquired by the optical sensor, after the host performs judgment, the controller spontaneously drives the camera to move, and manual adjustment is not needed.

Description

technical field [0001] The invention belongs to the technical field of face recognition and detection, and in particular relates to a facial expression analysis system of people in an assembly scene. Background technique [0002] People’s satisfaction with a large-scale event is often the most important thing for event organizers. Manual research is affected by factors such as slow speed and inaccurate statistics, and it is difficult to guarantee sufficient accuracy and high efficiency. Therefore, introducing machine vision technology into the analysis of people's satisfaction with activities, using machines to extract, analyze and count faces, replacing traditional manual research methods, will help improve research efficiency and work levels. [0003] Machine vision technology is a kind of visual science and engineering. Since the development of this technology in the 1950s, it has made great progress in the depth and breadth of research, and its application in biometrics ...

AI Technical Summary

Problems solved by technology

[0004] Traditional manual surveys have shortcomings such as poor timeliness, inaccurate survey results, and high survey costs. At present, there is no system on the market that simultaneously has the functions of face recognition, expression analysis, and data statistics.

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