Ehicle tracking based on video in fast traffic scenarios
Abstract
This paper is aiming at the problem of low tracking accuracy of moving vehicles in fast traffic scenarios, the ECO algorithm based on correlation filtering is applied to real-time tracking to achieve stable and accurate tracking of target vehicles. Through the factorized convolution operator, the extracted features are more comprehensive and efficient; the optimization of the training set effectively reduces redundancy; and the more representative correlation filter is used to prevent over-fitting; a simple update model is used to prevent model drift. The experimental results show that the proposed method finally achieved a tracking effect of 97% recognition rate.
- Publication:
-
Materials Science and Engineering Conference Series
- Pub Date:
- December 2019
- DOI:
- 10.1088/1757-899X/677/4/042118
- Bibcode:
- 2019MS&E..677d2118L