Original scientific paper
https://doi.org/10.1080/00051144.2018.1503137
Depth sensing with disparity space images and three-dimensional recursive search
Miroslav Rožić
; Zagrebačka Banka d.d., Zagreb, Croatia
Tomislav Pribanić
; Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
Abstract
We present a coarse-to-fine stereo matching optimization applicable to methods utilizing the Disparity Space Image (DSI) structure. With the Three-dimensional Recursive Search algorithm (3DRS), a coarse disparity seed is obtained first, with minimal computational effort. The coarse disparity seed is then used as a guidance to locally compute the DSI disparity space with a reduced number of disparity hypotheses, yielding significantly shorter execution times for the disparity computation. The method performance was measured on the well-known Dynamic Programming (DP) DSI-based method and the images from the Middlebury set. The DP method with the DSI optimization applied maintains or improves the overall level of disparity map accuracy while delivering a near sevenfold speed-up of execution in comparison to DP alone. We furthermore show that the optimized method’s performance does not depend on the expected input disparity range, which is commonly restricted, or expected to be defined upfront, for DSI-based stereo matching methods
Keywords
Stereo vision; disparity computation; dynamic programming; DSI; 3DRS; census transform
Hrčak ID:
225187
URI
Publication date:
28.9.2018.
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