Non-inductive face attendance checking method, device and equipment and storage medium

Abstract

The invention discloses a non-inductive attendance checking method, device and equipment and a computer readable storage medium, and the method comprises the steps: carrying out the face feature pointpositioning of images of continuous frames, extracting the face features of each frame of image through a convolutional neural network model, and storing the face features in a face feature list; clustering the face feature list to obtain a face feature matrix; carrying out face image quality analysis on the face features in the face feature matrix; obtaining an image quality value correspondingto the human face feature, constructing a quality analysis matrix, matching the human face feature in the human face feature matrix with an original human face feature stored in a preset original human face database, obtaining a matching result of the human face feature, and storing the matching result in an identification similarity matrix; and obtaining a face attendance result according to thequality analysis matrix and the recognition similarity matrix, and performing face recognition on the multi-person multi-frame image by adopting an image quality analysis method in combination with aface feature clustering method, so that the face recognition precision in the face attendance checking process is effectively improved.

Description

technical field [0001] The present invention relates to the field of computer image processing, in particular to a method, device, equipment and computer-readable storage medium for non-sensing face attendance checking. Background technique [0002] The traditional attendance method is fingerprint check-in. Fingerprint check-in will undoubtedly cause congestion due to queuing during the peak hours of work. With the continuous advancement of artificial intelligence technology, face-based attendance has become a reality. An important technology involved in face attendance is face image matching. [0003] At present, in the process of using ordinary cameras to check attendance, many people often appear in the camera at the same time, and the camera will capture all the frames of the attendanceee from entering the door to disappearing from the camera. In addition, due to weather changes and the change of wearing glasses and hats by the attendees, the recognition rate will decre...

AI Technical Summary

Problems solved by technology

[0003] At present, in the process of using ordinary cameras to check attendance, many people often appear in the camera at the same time, and the camera will capture all the frames of the attendanceee from entering the door to disappearing from the camera. In addition, due to changes in the weather and changing glasses and hats by the attendees, the recognition rate will decrease and the recognition results will be diversified.

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