Southall, B., Bansal, M., & Eledath, J., (June 2009). “Real-time vehicle detection for highway driving,” Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, vol., no., pp.541,548, 20-25.
We present a new multi-stage algorithm for car and truck detection from a moving vehicle. The algorithm performs a search for pertinent features in three dimensions, guided by a ground plane and lane boundary estimation sub-system, and assembles these features into vehicle hypotheses. A number of classifiers are applied to the hypotheses in order to remove false detections. Quantitative analysis on real-world test data show a detection rate of 99.4% and a false positive rate of 1.77%; a result that compares favourably with other systems in the literature.