Efficient methods using slanted support windows for slanted surfaces

The frontal‐parallel assumption is made by many matching algorithms, but this assumption fails for slanted surfaces. This study proposes a matching algorithm intended to improve the matching results for slanted surfaces. First, a mathematical model is constructed to prove that slanted surfaces in the environment have corresponding slanted disparity surfaces in the disparity space image, and the model is to help find the proper plane parameters of slanted support windows, then improved cost aggregation and post‐processing methods are proposed. The algorithm is tested using the Middlebury and Karlsruhe Institute of Technology and Toyota Technical Institute at Chicago (KITTI) benchmarks. The results demonstrate that the algorithm exhibits good performance and is efficient for slanted surfaces.