Human face recognition method and system thereof

Abstract

The invention discloses a human face recognition method, which has the characteristics of self-learning function and space-time property. According to the human face recognition method, human face recognition is realized by the steps of human face detection, human face tracking, data acquisition and analysis, recognition, online learning, human-machine interaction. The invention further discloses a system for realizing the human face recognition method. The system comprises a detector, a tracker, a collector, an analyzer, an online learning module, a recognizer and a human-machine interaction module. Compared with the prior art, the human face recognition method and human face recognition system have the advantages of strong anti-interference capability and high recognition efficiency.

Description

technical field [0001] The invention relates to human-computer interaction technology, in particular to a face recognition method and system thereof. Background technique [0002] Human-computer interaction is currently a hot spot in the field of computer science research in the world. In human-computer interaction technology, face recognition is gradually being applied to smart home and other occasions as the most convenient method for computers to identify users and provide personalized services. Face recognition based on computer vision, its core is to use computer vision, image processing and other technologies to process the video sequences collected by image acquisition equipment, and classify users, so as to respond accordingly. [0003] In the existing face recognition technology, the detection of faces, the tracking of detected faces, the extraction of face features from a given image or video sequence and comparison with face database data have been realized respe...

AI Technical Summary

Problems solved by technology

However, the current traditional face recognition system cannot integrate some technologies with better effects into modules, so there are the following problems:

[0004] (1) Poor effect

Because the traditional face recognition system cannot effectively integrate the various modules of the face recognition system, the traditional face recognition system is prone to problems such as missing faces, tracking drift, unrecognizable, uncertain, or even errors, which seriously affect people. face recognition effect

[0005] (2) Poor interactivity

Traditional face recognition systems cannot interact with people well

When the face cannot be recognized, is uncertain or even makes mistakes, the system cannot interact with people well, so when the recognition is inaccurate, the system cannot get feedback from the user in time, and the performance cannot be improved; even when the recognition is inaccurate Sometimes, because the system thinks that its own recognition is correct and uses the recognition result to modify the original parameters in the system (that is, self-learning), the more the system is used, the worse it becomes.

[0006] (3) Poor adaptability

Traditional face recognition systems are easily affected by various external conditions such as light, beards, glasses, hairstyles, expressions, etc., reducing the recognition rate

Therefore, the system is not very practical

Images