Title :
Estimation of number of people in crowded scenes using perspective transformation
Author :
Lin, Sheng-Fuu ; Chen, Jaw-Yeh ; Chao, Hung-Xin
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
fDate :
11/1/2001 12:00:00 AM
Abstract :
In the past, the estimation of crowd density has become an important topic in the field of automatic surveillance systems. In this paper, the developed system goes one step further to estimate the number of people in crowded scenes in a complex background by using a single image. Therefore, more valuable information than crowd density can be obtained. There are two major steps in this system: recognition of the head-like contour and estimation of crowd size. First, the Haar wavelet transform is used to extract the featured area of the head-like contour, and then the support vector machine is used to classify these featured area as the contour of a head or not. Next, the perspective transforming technique of computer vision is used to estimate crowd size more accurately. Finally, a model world is constructed to test this proposed system and the system is also applied for real-world images
Keywords :
computer vision; edge detection; feature extraction; neural nets; object recognition; surveillance; wavelet transforms; Haar wavelet transform; complex background; computer vision; contour recognition; crowd density estimation; crowd size; crowded scenes; feature extraction; perspective transform; support vector machine; surveillance; Computer vision; Data mining; Feature extraction; Layout; Magnetic heads; Support vector machine classification; Support vector machines; Surveillance; System testing; Wavelet transforms;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/3468.983420
