Imperial College London

Professor Yiannis Demiris

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Human-Centred Robotics, Head of ISN
 
 
 
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Contact

 

+44 (0)20 7594 6300y.demiris Website

 
 
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Location

 

1014Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Choi:2016:10.1109/CVPR.2016.468,
author = {Choi, J and Chang, HJ and Jeong, J and Demiris, Y and Choi, JY and Choi, J and Chang, H and Jeong, J and Demiris, Y and Choi, JY},
doi = {10.1109/CVPR.2016.468},
pages = {4321--4330},
publisher = {IEEE},
title = {Visual Tracking Using Attention-Modulated Disintegration and Integration},
url = {http://dx.doi.org/10.1109/CVPR.2016.468},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - In this paper, we present a novel attention-modulatedvisual tracking algorithm that decomposes an object intointo 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. Inthe integration stage it recombines the units to memorizeand recognize the target object effectively. With respectto the elementary trackers, we present a novel attentionalfeature-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 trackingbenchmark datasets.
AU - Choi,J
AU - Chang,HJ
AU - Jeong,J
AU - Demiris,Y
AU - Choi,JY
AU - Choi,J
AU - Chang,H
AU - Jeong,J
AU - Demiris,Y
AU - Choi,JY
DO - 10.1109/CVPR.2016.468
EP - 4330
PB - IEEE
PY - 2016///
SN - 1063-6919
SP - 4321
TI - Visual Tracking Using Attention-Modulated Disintegration and Integration
UR - http://dx.doi.org/10.1109/CVPR.2016.468
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000400012304042&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://ieeexplore.ieee.org/document/7780837/
UR - http://hdl.handle.net/10044/1/30903
ER -