In search of a car utilizing a 3D model with context for object detection

Automatic video analysis of interactions between road users is desired for city and road planning. A first step of such a system is object localization of road users. In this work, we present a method of detecting a specific car in an intersection from a monocular camera image. A camera calibration and segmentation are utilized as inputs by the method in order to detect a car. Using these inputs, a sampled search space in the ground plane, including rotations, is explored with a 3D model of a car in order to produce output in form of rectangle detections in the ground plane. Evaluation on real recorded data, with ground truth for one car using GPS, indicates that a car can be detected in over 90% of the time with an average error around 0.5m.