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