Authors:
Iman Alikhani
1
;
Hamed R.-Tavakoli
2
;
Esa Rahtu
1
and
Jorma Laaksonen
2
Affiliations:
1
University of Oulu, Finland
;
2
Aalto University, Finland
Keyword(s):
Saliency, Mean-shift Tracking, Target Representation.
Related
Ontology
Subjects/Areas/Topics:
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
;
Visual Attention and Image Saliency
Abstract:
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 & robustness; and discuss the usefulness of saliency-based target
tracking.
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