Title :
A Low-Cost Pedestrian Detection System with a Single Optical Camera
Author :
Xu, Y.W. ; Cao, X.B. ; Qiao, H.
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China
Abstract :
This paper presents a low-cost solution for pedestrian detection using a single optical video camera on a moving vehicle. Since only one optical camera can collect just a little original information, our system scan two sequential frames to get both appearance and motion information. We use zoom image and slide window techniques to select the objective region, apply a cascaded classifier combined with statistical learning and SVM to recognize human body, adopt zoom-scale to estimate the distance from a pedestrian and develop a distance transform algorithm to forecast his/her orientation. This system is suitable for detecting pedestrians in the range of 0.3-20 meters in the city traffic with the speed under 50 km/h. The test with videos of real city traffic indicates that our system has got acceptable detecting rate and processing speed
Keywords :
image classification; image motion analysis; object detection; road vehicles; statistical analysis; support vector machines; traffic engineering computing; transforms; video cameras; cascaded classifier; city traffic; distance transform; human body recognition; motion information; optical video camera; pedestrian detection system; pedestrian orientation; road vehicle; slide window; statistical learning; support vector machine; zoom image; Cameras; Cities and towns; Humans; Image recognition; Statistical learning; Support vector machine classification; Support vector machines; System testing; Vehicle detection; Vehicles; Pedestrian detection system; cascaded classifier; decomposed SVM; distance transform algorithm; statistical learning;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713692
