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