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
|Author:||Alikhani, Iman1; R.-Tavakoli, Hamed2; Rahtu, Esa3;|
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
|Online Access:||PDF Full Text (PDF, 0.1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201702171773
Science and Technology Publications,
|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.
|Pages:||17 - 21|
Proceedings of the 11th joint conference on computer vision, imaging and computer graphics theory and applications
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
Hamed R.-Tavakoli and Jorma Laaksonen were supported by The Academy of Finland under the Finnish Center of Excellence in Computational Inference Research (COIN).
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Published in this repository with the kind permission of the publisher.