DocumentCode :
3159589
Title :
A neural network approach for counting pedestrians from video sequence images
Author :
Ikeda, Norifumi ; Saitoh, Ayumu ; Isokawa, Teijiro ; Kamiura, Naotake ; Metsui, N.
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji
fYear :
2008
fDate :
20-22 Aug. 2008
Firstpage :
2485
Lastpage :
2488
Abstract :
A system for counting pedestrians in sequence images obtained from single video camera is proposed in this paper. This system has the capabilities of simultaneously detecting and tracking several groups of pedestrians. Groups can be extracted by using the background subtraction method, and a layered neural network with BP learning algorithm is applied to estimate the number of pedestrians in each of the groups. The practical applicability of the proposed system is demonstrated, applying it to the sequence images of a real scenery.
Keywords :
backpropagation; feature extraction; image sequences; neural nets; object detection; target tracking; video signal processing; BP learning algorithm; background subtraction method; group extraction; layered neural network; pedestrian counting; pedestrian detection; pedestrian number estimation; pedestrian tracking; video camera; video sequence images; Cameras; Computational efficiency; Computer networks; Data mining; Electronic mail; Humans; Layout; Neural networks; Surveillance; Video sequences; Pedestrian; detection; layered neural network; tracking; video sequence images;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual Conference, 2008
Conference_Location :
Tokyo
Print_ISBN :
978-4-907764-30-2
Electronic_ISBN :
978-4-907764-29-6
Type :
conf
DOI :
10.1109/SICE.2008.4655083
Filename :
4655083
Link To Document :
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