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

@article{Lee:2015:10.1109/TIP.2015.2487837,
author = {Lee, K and Ognibene, D and Chang, HJ and Kim, T-K and Demiris, Y and Lee, K and Ognibene, D and Chang, HJ and Kim, TK and Demiris, Y and Lee, K and Ognibene, D and Chang, HJ and Kim, T-K and Demiris, Y and Lee, K and Ognibene, D and Chang, H and Kim, T-K and Demiris, Y},
doi = {10.1109/TIP.2015.2487837},
journal = {IEEE TRANSACTIONS ON IMAGE PROCESSING},
pages = {5916--5927},
title = {STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection},
url = {http://dx.doi.org/10.1109/TIP.2015.2487837},
volume = {24},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - © 2015 IEEE. We present a spatiooral attention relocation (STARE) method, an information-theoretic approach for efficient detection of simultaneously occurring structured activities. Given multiple human activities in a scene, our method dynamically focuses on the currently most informative activity. Each activity can be detected without complete observation, as the structure of sequential actions plays an important role on making the system robust to unattended observations. For such systems, the ability to decide where and when to focus is crucial to achieving high detection performances under resource bounded condition. Our main contributions can be summarized as follows: 1) information-theoretic dynamic attention relocation framework that allows the detection of multiple activities efficiently by exploiting the activity structure information and 2) a new high-resolution data set of temporally-structured concurrent activities. Our experiments on applications show that the STARE method performs efficiently while maintaining a reasonable level of accuracy.
AU - Lee,K
AU - Ognibene,D
AU - Chang,HJ
AU - Kim,T-K
AU - Demiris,Y
AU - Lee,K
AU - Ognibene,D
AU - Chang,HJ
AU - Kim,TK
AU - Demiris,Y
AU - Lee,K
AU - Ognibene,D
AU - Chang,HJ
AU - Kim,T-K
AU - Demiris,Y
AU - Lee,K
AU - Ognibene,D
AU - Chang,H
AU - Kim,T-K
AU - Demiris,Y
DO - 10.1109/TIP.2015.2487837
EP - 5927
PY - 2015///
SN - 1057-7149
SP - 5916
TI - STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection
T2 - IEEE TRANSACTIONS ON IMAGE PROCESSING
UR - http://dx.doi.org/10.1109/TIP.2015.2487837
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000369538200013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/27670
VL - 24
ER -