DocumentCode :
2423587
Title :
A People-Counting System Based on BP Neural Network
Author :
Li, Na-Na ; Song, Jie ; Zhou, Rui-Ying ; Gu, Jun-hua
Author_Institution :
Tianjin Univ., Tianjin
Volume :
3
fYear :
2007
fDate :
24-27 Aug. 2007
Firstpage :
283
Lastpage :
287
Abstract :
A people-counting system based on a back propagation (BP) neural network is proposed in this paper. The proposed system uses cheap photoelectric sensor to collect data and introduces BP neural network for counting and recognition, and it is effective and flexible for the purpose of performing people counting. In this paper, new methods for segmentation and feature extraction are developed to enhance the classification performance. Promising results were obtained and the analysis indicates that the proposed system based on BP neural network provides good results with low false rate and it is effective for people-counting.
Keywords :
backpropagation; neural nets; traffic engineering computing; BP neural network; backpropagation neural network; feature extraction; people-counting system; photoelectric sensor; Computer networks; Costs; Feature extraction; Information analysis; Infrared sensors; Intelligent sensors; Monitoring; Neural networks; Sensor systems; Signal generators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
Type :
conf
DOI :
10.1109/FSKD.2007.107
Filename :
4406245
Link To Document :
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