Adaptive Target Detection and Matching for a Pedestrian Tracking System

We present a 3D tracking system for detecting and tracking multiple targets. An extended Kalman Filter (EKF) is used to maintain each target´s 3D state and provide location predictions to the pattern matchers whose task it is to follow the targets in images. An adaptive background modeling algorithm is used together with the tracking process to detect moving objects in complex environments. We propose a warping-based pattern matching approach to deal with object deformation during tracking. We present examples of results of our tracker for outdoor scenes.