Behaviour pattern recognition of video image based on computer vision technology
by Fan Jiang; Yi Yu
International Journal of Information and Communication Technology (IJICT), Vol. 19, No. 1, 2021

Abstract: Aiming at the problems of low tracking accuracy, low recognition accuracy and low recognition efficiency in the traditional video image behaviour pattern recognition and analysis methods, a video image behaviour pattern recognition and analysis method based on computer vision technology is proposed. Through the computer vision technology to obtain the video image information, and to process the collected video image, combined with the automatic selection of tracking region algorithm and particle filter algorithm, on the basis of the target colour distribution model, to track the target in the video image. According to the extracted video image features, a multi example learning model is constructed, and the feature samples are selected to solve the positive sample set, and the results are input into the multi example SVM classifier to complete the recognition and analysis of video image behaviour. The experimental results show that the proposed method takes less than 2s to identify the target, and has high target tracking accuracy, recognition accuracy and recognition efficiency.

Online publication date: Wed, 28-Jul-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Communication Technology (IJICT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com