Target tracking based on data fusion tree in intelligent space

This paper puts forward a novel method based on multilevel information fusion to realize the real-time target detection and tracking. Based on the triangulation technique and least square method, the system matches the moving target by the information on color, and carries out the 3D reconstruction of target. Firstly, when the moving target is detected, the system will scan target human´s leg by laser range finder to cluster the nearest neighbor, and the exact distance information will be got. Secondly, this article adopts a better Extend Kalman Filter for heterogeneous sensor information fusion to realize the simultaneous robot localization and target tracking in intelligent space. At last, the experimental results verify the effectiveness of the proposed method.