Video sequences of road and traffic scenes are currently used for various purposes, such as studies of the traffic character of freeways. The task of this project is to automatically estimate vehicle speed from video sequences, acquired with a downward tilted camera from a bridge. Assuming that the studied road segment is planar and straight, the vanishing point in the road direction is extracted automatically by exploiting lane demarcations. Thus, the projective distortion of the road surface can be removed allowing affine rectification. Consequently, given one known ground distance along the road axis, 1D measurement of vehicle position in the correctly scaled road direction is possible. Vehicles are automatically detected and tracked along frames. First, the background image (the unoccupied road) is created from several frames by an iterative per channel exclusion of outlying colour values based on thresholding. Next, the subtraction of the background image from the current frame is binarized, and morphological filters are employed for vehicle clustering. At the lowest part of vehicle clusters a window is defined for normalised cross-correlation among frames to allow vehicle tracking. Additional orientations of the video camera, generating images with two vanishing points, have also been studied and exploited.
2005 Automatic estimation of vehicle speed from uncalibrated video sequences. L. Grammatikopoulos, G. Karras, E. Petsa. Proc. International Symposium on Modern Technologies, Education and Professional Practice in Geodesy and Related Fields, Sofia, 03 – 04 November, pp. 332-338.
2002 Geometric information from single uncalibrated images of roads. L. Grammatikopoulos, G. Karras, E. Petsa. International Archives of Photogrammetry & Remote Sensing, 34(B5), pp. 21-26