Camera calibration and near-view vehicle speed estimation

Futang Peng; Changsong Liu; Xiaoqing Ding

doi:10.1117/12.765077

26 February 2008 Camera calibration and near-view vehicle speed estimation

Futang Peng, Changsong Liu, Xiaoqing Ding

Proceedings Volume 6813, Image Processing: Machine Vision Applications; 681314 (2008) https://doi.org/10.1117/12.765077
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

In this paper, we present an algorithm of estimating new-view vehicle speed. Different from far-view scenario, near-view image provides more specific vehicle information such as body texture and vehicle identifier which makes it practical for individual vehicle speed estimation. The algorithm adopts the idea of Vanishing Point to calibrate camera parameters and Gaussian Mixture Model (GMM) to detect moving vehicles. After calibrating, it transforms image coordinates to the real-world coordinates using a simple model - the Pinhole Model and calculates the vehicle speed in real-world coordinates. Adopting the idea of Vanishing Point, this algorithm only needs two pre-measured parameters: camera height and distance between camera and middle road line, other information such as camera orientation, focal length, and vehicle speed can be extracted from video data.

Citation Download Citation

Futang Peng, Changsong Liu, and Xiaoqing Ding "Camera calibration and near-view vehicle speed estimation", Proc. SPIE 6813, Image Processing: Machine Vision Applications, 681314 (26 February 2008); https://doi.org/10.1117/12.765077

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