DocumentCode :
3592327
Title :
Infrared passenger flow collection system based on RBF neural net
Author :
Song, Jie ; Dong, Yong-Feng ; Yang, Xin-wei ; Gu, Jun-hua ; Fan, Pei-pei
Author_Institution :
Sch. of Comput. Sci. & Software, Hebei Univ. of Technol., Tianjin
Volume :
3
fYear :
2008
Firstpage :
1277
Lastpage :
1281
Abstract :
As the current level of the people-counting, on the consideration of the cost of the acquisition equipment and the acquisition accuracy, the customer-counting system is constructed based on RBF neural net using technology of infrared photoelectric sensor. For better differential count, extant data segmentation and the method of feature extraction is improved based on the feature of passenger-counting data continuous space-time sequence. Compared with traditional customer-counting using sensor, the accuracy of real-time customer-counting is improved in this method and the situation of customers who entry at the same time can be identified with lower error rate. It is helpful for both principle research and actual application.
Keywords :
feature extraction; infrared detectors; photodetectors; radial basis function networks; traffic engineering computing; RBF neural net; acquisition accuracy; acquisition equipment; continuous space-time sequence; customer counting system; differential count; extant data segmentation; feature extraction; infrared passenger flow collection system; infrared photoelectric sensor; people counting; Costs; Cybernetics; Data acquisition; Error analysis; Feature extraction; Infrared detectors; Infrared sensors; Machine learning; Neural networks; Sensor systems; Passenger flow; RBF Neural network; Segmentation; feature extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620601
Filename :
4620601
Link To Document :
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