جهت دسترسی به کاربرگه ی زیر، از این لینک استفاده کنید. http://dl.pgu.ac.ir/handle/Hannan/73906
Title: Visual tracking using attention-modulated disintegration and integration
Issue Date: 12-Dec-2016
2-Mar-2016
Publisher: IEEE
Description: In this paper, we present a novel attention-modulated visual tracking algorithm that decomposes an object into into multiple cognitive units, and trains multiple elemen- tary trackers in order to modulate the distribution of at- tention according to various feature and kernel types. In the integration stage it recombines the units to memorize and recognize the target object effectively. With respect to the elementary trackers, we present a novel attentional feature-based correlation filter (AtCF) that focuses on dis- tinctive attentional features. The effectiveness of the pro- posed algorithm is validated through experimental compar- ison with state-of-the-art methods on widely-used tracking benchmark datasets.
Other Identifiers: http://ieeexplore.ieee.org/document/7780837/
1063-6919
http://hdl.handle.net/10044/1/30903
https://dx.doi.org/10.1109/CVPR.2016.468
612139
Type Of Material: OTHER
Appears in Collections:Faculty of Engineering

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