A new method of image features pre-selection for real-time pose estimation based on Kalman filter

The problem of real-time pose estimation of moving objects using a stereo video camera system is considered in this paper. A computationally efficient algorithm is proposed based on Kalman filtering of the position measurements of suitable feature points selected on the target objects. The efficiency of the algorithm is improved by adopting a new pre-selection technique of the feature points, based on binary space partition (BSP) trees, which takes advantage of the Kalman filter prediction capability. Computer simulations are presented.