Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/79745
Citations | ||
Scopus | Web of ScienceĀ® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Edge detection techniques assisted target tracking algorithm |
Author: | Xu, Xu Guo, Shuxu Ding, Yinhao |
Citation: | Advances in Information Sciences and Services, 2013; 5(7):138-145 |
Publisher: | Advanced Institute of Convergence Information Technology (AICIT) |
Issue Date: | 2013 |
ISSN: | 1976-3700 |
School/Discipline: | School of Electrical and Electronic Engineering |
Statement of Responsibility: | Xu Xu, Shuxu Guo, Yinhao Ding |
Abstract: | This paper proposes an improved approach for target tracking. The new approach addresses the tracking failure issue of Mean-shift algorithm when the dimension of an object changes over time. Object edge detection is implemented into the tracking process. The target can be located more accurately with an adaptive correction system based on the information of object edges. In addition, an improved edge detection algorithm is also studied to overcome the problem of low tracking accuracy in traditional methods. The experiments demonstrate that, compared with the traditional Mean-shift algorithm, the proposed approach can significantly improve the performance in tracking accuracy. |
Keywords: | Object Tracking; Edge Detection; Mean-Shift |
Rights: | Copyright status unknown |
DOI: | 10.4156/AISS.vol5.issue7.17 |
Appears in Collections: | Electrical and Electronic Engineering publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.