MODEL-BASED VEHICLE DETECTION AND CLASSIFICATION USING ORTHOGRAPHIC APPROXIMATIONS

This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a realt ime system intended to provide continuous monitoring and classificatio n of traffic from a fixed camera on a busy multi-lane motorway. The ma in constraints of the system design were: (i) all low level processing is to be carried out by low-cost auxiliary hardware; (ii) all 3-D rea soning is to be carried out automatically off-line, at set-up time. Th e system developed uses three main stages: (i) pose and model hypothes is using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) and (iii) have radicall y different computing performance and computational costs. and need to be carefully balanced for efficiency. Together, they provide an effec tive way to locate, track and classify vehicles. (C) 1997 Elsevier Sci ence B.V.