Real-Time Visual Tracking of 3D-Objects
The use of visual sensors may have high impact in applications where it ist required to measure the pose (position and orientation) and the visual features of object moving in unstructured environments. In robotics, the measurement provided by video cameras can be directly used to perform closed-loop control of the robot end-effector pose. In this chapter the problem of real-time estimation of the position and orientation of a moving object using a fixed stereo camera system is considered. An approach based on the use of the Extended Kalman Filter (EKF) combined with a 3D representation of the objects geometry based on Binary Space Partition (BSP) trees ist illustrated. The performance of the proposed visual tracking algorithm is experimentally tested in the case of an object moving in the visible space of a fixed stereo camera system.
KeywordsFeature Point Selection Algorithm Extend Kalman Filter Visual Tracking Visual Servoing
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