Human tracking by a mobile robot using 3D features

Detection and Tracking of human being is a very important problem in Computer Vision. Human robot interaction is a very essential need for service robots where robots are required to detect and track human beings in order to provide the required service. In this paper we present an improved novel approach for tracking a target person in crowded environment. We used multi-sensor data fusion approach by combining the data of stereo camera and laser rangefinder (LRF) to perform human tracking. The system gathers the features of human upper body, face and legs in the target person selection phase and then the robot will start following the target person. Camera is used for upper body and face detection while laser rangefinder is used for gathering legs data. Template matching and triangulation is done in order to get the dimensions of upper body and face. Target person tracking is done using Cam shift tracker. Thus our method presents a novel approach that uses all these techniques to track a target person in a crowded environment.