DocumentCode
2852528
Title
Pedestrian detection in nighttime driving
Author
Tian, Q.M. ; Luo, Y.P. ; Hu, D.C.
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear
2004
fDate
18-20 Dec. 2004
Firstpage
116
Lastpage
119
Abstract
This paper presents an approach for pedestrian detection in the nighttime driving with a normal camera. Bright objects in the video are extracted with an adaptive thresholding segmentation algorithm. Then, the size, position, and shape of each object are analyzed to judge whether it is a pedestrian. A tracking module is used to verify the result at last. Experimental results show that the proposed method can detect 71.26% pedestrians.
Keywords
automated highways; cameras; feature extraction; image segmentation; object detection; video signal processing; adaptive thresholding segmentation algorithm; image recognition; nighttime driving; pedestrian detection; support vector machine; tracking module; Cameras; Feedforward neural networks; Head; Infrared detectors; Neural networks; Object detection; Pattern recognition; Phase detection; Roads; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics (ICIG'04), Third International Conference on
Conference_Location
Hong Kong, China
Print_ISBN
0-7695-2244-0
Type
conf
DOI
10.1109/ICIG.2004.111
Filename
1410400
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