Detection System for Real-time Human Body

Abstract

The invention relates to a detection system for real-time human body, including gear shafts, the gear shaft is fixedly arranged on the wall surface, a first support bar and a second support bar are arranged on the gear shaft, the first support bar, one end of the second support bar is respectively provided with a first detection camera, second detection camera, the first detection camera, an imageacquisition module,a judgment processing module,a rotating module, a face recognition module are included in the second detection camera. The gear shaft can rotate and drive the first detection camera, as the second detect camera rotates at 360 degrees, compared with the prior art, the present invention improves the face recognition efficiency, and collects a face image of a person through the detecting camera rotates at 360 degrees, further improving the quality of acquiring the face image, thereby improving the face recognition accuracy.

Description

technical field [0001] The invention belongs to the technical field of face recognition, in particular to a real-time human body detection system. Background technique [0002] At present, face recognition technology has gradually become a low-level application tool technology with the maturity of conditions such as cameras, algorithms, and data volume, and has been continuously popularized. [0003] Among them, the face recognition technology is characterized by convenient feature collection and sanitation. In the prior art, the face recognition process usually includes several steps: image acquisition, image processing, feature extraction and face recognition. Wherein, the image acquisition step is used to obtain the face image; the image processing step is used to perform preprocessing on the face image such as curved noise and face alignment; the feature extraction step is used to extract the person in the pre-processed image according to a preset model. Face features: ...

AI Technical Summary

Problems solved by technology

[0004] With the development and promotion of artificial intelligence equipment, the application of electronic equipment to obtain face images is becoming more and more widespread. However, when people walk with their heads down and play with mobile phones, it will directly affect the quality of electronic equipment to obtain facial images. Therefore, the existing electronic equipment Face images cannot be captured in all aspects, which directly affects the efficiency and accuracy of face recognition

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