Influence of Aggregating Window Size on Disparity Maps Obtained from Equal Baseline Multiple Camera Set (EBMCS)

This paper is concerned with obtaining disparity maps on the basis of images from Equal Baseline Multiple Camera Set (EBMCS). EBMCS consists of a central camera and side cameras. Algorithms for obtaining disparity maps with the use of EBMCS take advantage of aggregating windows similarly to stereo matching algorithms for a stereo camera, a camera matrix or a camera array. The paper analyzes the influence of aggregating window size on the quality of disparity maps. Experiments presented in this paper include Sum of Sum of Squared Differences (SSSD) and Sum of Sum of Absolute Differences (SSAD) matching cost functions. Results show that for EBMCS with five cameras the highest quality of disparity maps is obtained when the size of the aggregating window is on average over 55 % smaller than the size of the most effective window for a pair of cameras.