MOVING OBJECT DETECTION USING DYNAMIC 2(1/2)D DATA FOR ROBOT SURROUNDING FIELD MONITORING

摘要

For man-machine cooperation the detection of pose changes appearing as object motion is a crucial factor. Pre-veous approaches were based on luminance and chrominance data used for subsequent pose information extraction. In contrast we present an algorithm for the detection of moving objects for dynamic 2~(1/2)D data providing direct spatial information based on the non-parametric model approach proposed by Elgammal [3]. The data is obtained by a range camera of static pose viewing the scene. Giving the coarse data captured by the camera the algorithm takes advantage of the dynamic and spatial characteristics of the data by evaluating temporal variation distribution. To counter long time changes, iterative updating of the used background model is performed by a selective updating approach utilizing the probability estimate.