Authors:
Emre Tunali
;
Sinan Oz
and
Mustafa Eral
Affiliation:
ASELSAN Inc. Microelectronics and Guidance and Electro-Optics Division, Turkey
Keyword(s):
Real-time Object Tracking, Size Adaptive Tracking, Track Drift Compensation, Track Initialization Error Compensation, Joint Segmentation and Tracking.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
;
Visual Attention and Image Saliency
Abstract:
To enhance correlation filter (CF) based trackers with size adaptivity and more robustness; we propose a new
strategy which integrates an external segmentation methodology with CF based trackers in a closed feedback
loop. Employing this strategy both enables object size disclosure during tracking; and automatic alteration of
track models and parameters online in non-disturbing manner, yielding better target localization. Obviously,
consolidation of CF based trackers with these properties introduces much more robustness against track center
drifts and relaxes widespread perfectly centralized track initialization assumption. In other words, even if
track window center is given with certain offset to center of target object at track initialization; proposed
methodology achieves target centralization by aligning tracker template center with target center smoothly in
time. Experimental results indicates that proposed algorithm increases performance of CF trackers in terms of
accuracy and
robustness without disrupting their real-time processing capabilities.
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