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Memory-Based Attention Control for Activity Recognition at a Subway Station
April-June 2007 (vol. 14 no. 2)
pp. 38-49
ASCII Text
x 
 
Karl F. MacDorman, Hiroshi Nobuta, Satoshi Koizumi, Hiroshi Ishiguro, "Memory-Based Attention Control for Activity Recognition at a Subway Station," IEEE Multimedia, vol. 14, no. 2, pp. 38-49, April-June, 2007.
 
 
BibTex
x
 
@article{ 10.1109/MMUL.2007.39,
author = {Karl F. MacDorman and Hiroshi Nobuta and Satoshi Koizumi and Hiroshi Ishiguro},
title = {Memory-Based Attention Control for Activity Recognition at a Subway Station},
journal ={IEEE Multimedia},
volume = {14},
number = {2},
issn = {1070-986X},
year = {2007},
pages = {38-49},
doi = {http://doi.ieeecomputersociety.org/10.1109/MMUL.2007.39},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Multimedia
TI - Memory-Based Attention Control for Activity Recognition at a Subway Station
IS - 2
SN - 1070-986X
SP38
EP49
EPD - 38-49
A1 - Karl F. MacDorman,
A1 - Hiroshi Nobuta,
A1 - Satoshi Koizumi,
A1 - Hiroshi Ishiguro,
PY - 2007
KW - distributed vision
KW - feature extraction
KW - human activity recognition
KW - omnidirectional
KW - support vector machines
KW - video surveillance
VL - 14
JA - IEEE Multimedia
ER -
 
Karl F. MacDorman, Indiana University
Hiroshi Nobuta, Wakayama University
Satoshi Koizumi, Advanced Telecommunications Research Institute
Hiroshi Ishiguro, Osaka University
The authors discuss Digital City Surveillance, their multicamera system that uses a new calibration-free behavior recognition method for monitoring human activity at a subway station.
Index Terms:
distributed vision, feature extraction, human activity recognition, omnidirectional, support vector machines, video surveillance
Citation:
Karl F. MacDorman, Hiroshi Nobuta, Satoshi Koizumi, Hiroshi Ishiguro, "Memory-Based Attention Control for Activity Recognition at a Subway Station," IEEE Multimedia, vol. 14, no. 2, pp. 38-49, Apr.-June 2007, doi:10.1109/MMUL.2007.39
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