Visual tracking using attention-modulated disintegration and integration

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Title: Visual tracking using attention-modulated disintegration and integration
Authors: Choi, J
Chang, H
Jeong, J
Demiris, Y
Choi, JY
Item Type: Conference Paper
Abstract: 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.
Issue Date: 12-Dec-2016
Date of Acceptance: 2-Mar-2016
ISSN: 1063-6919
Publisher: IEEE
Journal / Book Title: Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on
Copyright Statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 612139
Conference Name: IEEE Conference on Computer Vision and Pattern Recognition
Publication Status: Published
Start Date: 2016-06-26
Finish Date: 2016-07-01
Conference Place: Las Vegas, USA
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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