Target tracking and recognition of a moving video image based on convolution feature selection
by Jun Wei Yang
International Journal of Biometrics (IJBM), Vol. 13, No. 2/3, 2021

Abstract: In order to overcome the low accuracy of moving video image target tracking and recognition, a method of moving video image target tracking and recognition based on convolution feature selection is proposed. In this method, feature centres are generated according to the distance matrix between feature images, and feature dimensions are compressed. The multi-layer convolution feature is used to train multiple trackers to jointly determine the target state. The weight of the tracker is updated online by the real-time error of the tracker, and the information redundancy and noise between different convolution features are filtered out. The experimental results show that the recall rate is close to 100% of the success rate of the tracker, the recognition error rate is close to 0, and the recognition time is less than 0.5 min, which can effectively improve the recognition accuracy. At the same time, the whole algorithm has strong adaptability.

Online publication date: Thu, 29-Apr-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 Biometrics (IJBM):
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