Abstract
To ensure the safety and efficiency of the pedestrian traffic, this paper presents a real-time system for moving pedestrian detection and tracking in sequences of images of outdoor scenes acquired by a stationary camera. The self-adaptive background subtraction method and the dynamic multi-threshold method were adopted here for background subtraction and image segmentation. During the process of tracking, a new method based on gray model GM(1,1) was proposed to predict the motion of pedestrians. And then a template for tracking pedestrian continuously was presented by fusing several characters of targets. Experimental results of two real urban traffic scenes demonstrate the efficiency of this method, then the application of this method is discussed in real transportation system.
Supported by the national natural science foundation of China (Grant NO. 60134010).
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© 2006 Springer-Verlag Berlin Heidelberg
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Hao-li, C., Zhong-ke, S., Qing-hua, F. (2006). The Study of the Detection and Tracking of Moving Pedestrian Using Monocular-Vision. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11758549_117
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DOI: https://doi.org/10.1007/11758549_117
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