Vehicle detection and tracking at intersections by fusing multiple camera views
Elias Strigel, Daniel Meißner, Klaus Dietmayer · 2013
Intersections are challenging locations for drivers. Complex situations are common due to the variety of road users and intersection layouts. This contribution describes a real time method for detecting and tracking vehicles at intersections using images captured by a static camera network. After background subtraction, the foreground segments are projected on a common fusion map. Using this fusion map, the pose, width, and height of the vehicles can be determined. After that, the detected objects are tracked by a Gaussian-Mixture approximation of the Probability Hypothesis Density filter. Results of the intersection perception can further be communicated to equipped vehicles by wireless communication.