A new algorithm for vehicle velocity calculation though automatic and dynamic camera calibration is presented in this paper.The algorithm is based on distance information in the light transmission model and a camera linear model under homogenous fog.Unlike previously published works

the factor of homogenous fog is added into our traffic model. Only road plane and moving foreground are included

while painted lines and other traffic prior information could be neglected. Three major steps construct our algorithm. First

an area search method (ASM) based on activity map recognizes the current weather condition.The current weather condition is assumed to be homogenous fog if the average pixel value from top to bo-ttom in a selected area of interest changes in the form of an edge spread function. Second

using a dark channel prior algorithm a transmission image is calculated.Intrinsic and extrinsic parameters of the camera are calculated based on the para-meter calculation formula especially for our monocular model. In this step

eight key points with special transmittance for generating necessary calculation equations are selected to calibrate the camera. The mean velocity is retrieved based on velocity calculation formula by transforming coordinates from the image plane to the world coordinate plane. At the end of this paper

calibration results and vehicles velocity data for nine vehicles in different weather conditions are given. Comparison with other algorithm verifies the effectiveness of this proposed algorithm.