This paper concerns model-based vision for road traffic scene analysis. A traffic vision system is described. The three main modules of the system are movement detection, vehicle localization and discrimination, and vehicle tracking. This paper outlines our work on the localization and discrimination module. Emphasis is on recovering 3-D poses of road vehicles in given image regions. Two classes of algorithms are described, one based on symbolic image features (line segments), and the other simply on image intensity gradients. A priori knowledge about traffic scenes and vehicles is exploited to improve the performance and efficiency of the algorithms. The algorithms are tested extensively with routine outdoor traffic images, and examples are included to demonstrate their principles.