Depth estimation through iterative filtering uses a filter that refines depth maps from previous iterations. Its basis is using a bilateral filter using two penalty descriptors, the color of a region and the similarity of two disparity-matched regions. This research is focused on finding improvements of this method, mostly using a hierarchical approach. We use previously conducted experiments to compare the improved method with the original method, as well well as comparing the new method with results from other methods.
Keywords: Disparity estimation, depth estimation, stereo, stereopsis, filtering, hierarchical
These are examples taken from the Middlebury Stereo Vision dataset.
