2D human body tracking with Structural Kalman filter

摘要

Tracking moving objects is one of the most important techniques in motion analysis and understanding, and it has many difficult problems to solve. Especially, estimating and identifying moving objects, when the background and moving objects vary dynamically, are very difficult. It is possible under such a complex environment that targets may disappear totally or partially due to occlusion by other objects. The Kalman filter has been used to estimate motion information and use the information in predicting the appearance of targets in the succeeding frames. In this paper, we propose another version of the Kalman filter, to be called Structural Kalman filter, which can successfully work its role of estimating motion information under such a deteriorating condition as occlusion. Experimental results show that the suggested approach is very effective in estimating and tracking non-rigid moving objects reliably.