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