Title :
A New Method for People-Counting Based on Support Vector Machine
Author :
Zhu, Fang ; Yang, Xinwei ; Gu, Junhua ; Yang, Ruixia
Author_Institution :
Inf. Eng. Inst., Hebei Univ. of Technol., Tianjin, China
Abstract :
This paper proposed a new method for infrared people-counting. According to the characteristics of the time continuous data collected by infrared sensors, the pattern recognition idea is introduced in the data processing procedure. After the special pretreatment, adaptive segmentation and feature extraction for the people-counting data, the feature vector is used as the inputs of the trained support vector machine classifier to classify and statistic the total number of the people who go through the infrared sensor area in a period of time. Compared with traditional people-counting using sensor, this method is more accurate and it can count the people number at the situation that several people go through the infrared sensor at the same time. Finally, the experiments indicate that the method can be applied in actual application.
Keywords :
feature extraction; image segmentation; infrared imaging; support vector machines; adaptive segmentation; data processing procedure; feature extraction; feature vector; infrared people-counting; infrared sensors; pattern recognition; support vector machine; time continuous data; Artificial intelligence; Computer science; Feature extraction; Infrared detectors; Infrared sensors; Intelligent networks; Paper technology; Software; Support vector machine classification; Support vector machines; SVM; data segmentation; feature extraction; people-counting;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.94
