Real-time robust tracking with part-based and spatio-temporal context Online publication date: Thu, 13-May-2021
by Yanxia Wei; Zhen Jiang; Junfeng Xiao; Xinli Xu
International Journal of Computer Applications in Technology (IJCAT), Vol. 65, No. 2, 2021
Abstract: Owing to the significant and excellent performance of correlation filter in the aspect of computation convenience, correlation filters based trackers have become increasingly popular in the visual object tracking community. However, complete or partial occlusion is one of the major factors that seriously impact the tracking performance in visual tracking. To address this issue, we propose a novel tracking algorithm that perfectly integrates the results from the global correlation and local correlation filters for estimating the more accurate position of target. Then, we introduce the occlusion detection mechanism to eliminate the occlusion impact on the final position of object. In addition, our proposed tracker employs the spatial geometric constraints among the global object and local patches of object for preserving the structure integration of object. For verifying our method, we conduct extensive qualitative and quantitative experiments on challenging benchmark image sequences.
Online publication date: Thu, 13-May-2021
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 Computer Applications in Technology (IJCAT):
Login with your Inderscience username and 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 firstname.lastname@example.org