资 源 简 介
We present a real-time model-based vision approach for detecting and tracking vehicles from a moving platform. It
was developed in the context of the CMU Navlab project and is intended to provide the Navlabs with situational
awareness in mixed trac. Tracking is done by combining a simple image processing technique with a 3D extended
Kalman lter and a measurement equation that projects from the 3D model to image space. No ground plane
assumption is made. The resulting system runs at frame rate or higher, and produces excellent estimates of road
curvature, distance to and relative speed of a tracked vehicle. We have complemented the tracker with a novel
machine learning based algorithm for car detection, the CANSS algorithm, which serves to initialize tracking
