Visual tracking of multiple objects using binary space partitioning trees

The use of visual sensors may have high impact in robotic applications where it is required to measure the pose (position and orientation) and the visual features of objects moving in unstructured environments. In this paper, the problem of real-time estimation of the position and orientation of of multiple objects is considered. Special emphasis is devoted to the case when two or more objects overlap with respect to the visual system causing occlusion. The algorithm is based on the Kalman filtering and Binary Space Partition (BSP) tree representations of the objects geometry. The real-time implementation of the algorithm is experimentally tested for the case of visual tracking of two objects using two cameras.