University of Oulu

Alikhani I., R.-Tavakoli H., Rahtu E. and Laaksonen J. (2016). On the Contribution of Saliency in Visual Tracking. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and ApplicationsISBN 978-989-758-175-5, pages 17-21. DOI: 10.5220/0005648900170021

On the contribution of saliency in visual tracking

Saved in:
Author: Alikhani, Iman1; R.-Tavakoli, Hamed2; Rahtu, Esa3;
Organizations: 1Department of Computer Science and Engineering, University of Oulu, Oulu, Finland
2Department of Computer Science, Aalto University, Espoo, Finland
3Center for Machine Vision Research, University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.1 MB)
Persistent link:
Language: English
Published: Science and Technology Publications, 2016
Publish Date: 2017-02-17


Visual target tracking is a long-standing problem in the domain of computer vision. There are numerous methods proposed over several years. A recent trend in visual tracking has been target representation and tracking using saliency models inspired by the attentive mechanism of the human. Motivated to investigate the usefulness of such target representation scheme, we study several target representation techniques for mean-shift tracking framework, where the feature space can include color, texture, saliency, and gradient orientation information. In particular, we study the usefulness of the joint distribution of color-texture, color-saliency, and color-orientation in comparison with the color distribution. The performance is evaluated using the visual object tracking (VOT) 2013 which provides a systematic mechanism and a database for the assessment of tracking algorithms. We summarize the results in terms of accuracy and robustness; and discuss the usefulness of saliency-based target t racking.

see all

ISBN: 978-989-758-175-5
Pages: 17 - 21
DOI: 10.5220/0005648900170021
Host publication: Proceedings of the 11th joint conference on computer vision, imaging and computer graphics theory and applications
Conference: Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: Hamed R.-Tavakoli and Jorma Laaksonen were supported by The Academy of Finland under the Finnish Center of Excellence in Computational Inference Research (COIN).
Copyright information: © 2016 SCITEPRESS, Science and Technology Publications, Lda - All rights reserved.
Published in this repository with the kind permission of the publisher.