Abstract. Using image sequences as input for vision-based algorithms allows the possibility of merging information from previous images into the analysis of the current image. In the context of video-based driver assistance systems, such temporal analysis can lead to the improvement of depth estimation of visible objects. This paper presents a Kalman filter-based approach that focuses on the reduction of uncertainty in disparity maps of image sequences. For each pixel in the current disparity map, we incorporate disparity data from neighbourhoods of corresponding pixels in the immediate previous and the current image frame. Similar approaches have been considered before that also use disparity information from previous images, but without complementing the analysis with data from neighbouring pixels
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.