Bayesian vehicle class recognition using 3-d probe

A new approach is presented to vehicle-class recognition from video clips. Two new concepts introduced are: probes consisting of local 3-d curve-groups which when projected into video frames are features for recognizing vehicle classes in video clips; and Bayesian recognition based on class probability densities for groups of 3-d distances between pairs of 3-d probes. A full Bayesian recognizer is realized via Monte Carlo simulation method. Also, a sub-optimal but robust camera calibration method is employed and tested extensively.