Skip to Main Content
Vehicles are indispensable in modern life. The capability of monitoring them over a long range can play significant roles in many surveillance applications. However, due to high mobility of vehicles, tracking them is difficult and we need to utilize a large network of cameras and reason on discrete sets of observations made from non-overlapping cameras. In this paper, we introduce enabling techniques for such a surveillance need. Specifically, we build explicit 3D models and use them for vehicle signature extraction and matching. The algorithm uses a single active shape model (ASM) for all consumer vehicles. After detecting presence of a vehicle, eg, by background subtraction, our algorithm then reconstructs a texture mapped 3D model. 3D car models enable us to monitor vehicles in many novel ways otherwise impossible. Two use cases are provided.