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An Improved TLD Tracking Method Using Compressive Sensing
2016
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
unpublished
Visual Tracking, as an important subject in computer vision, has been widely used in surveillance, space exploration, and human-computer interaction etc. Both tracking-learningdetection (TLD) [1] and compressive tracking (CT) [2] are successful algorithms among those proposed recently. However, TLD suffers from low efficiency and CT overlooks scale change during tracking. In this paper, we propose an improved TLD tracking algorithm by using compressive sensing. The improvements include
doi:10.2991/icaita-16.2016.64
fatcat:cjlhnuplh5c5vgtm6xcz5po3vu