3d Object–based Depth Estimation from Stereoscopic Image Sequences
نویسنده
چکیده
A 3D object–based depth estimation approach from stereoscopic image sequences is presented in this paper that introduces a memory for depth information from preceding image pairs. This approach is used in the EU–RACE project DISTIMA for applications like remote handling, quality control and TV post processing. Compared to depth estimation approaches that compute depth maps from consecutive stereoscopic image pairs independently by a triangulation of corresponding image points, the temporal coherence and accuracy of depth estimates is increased. The remaining depth estimation error variance is reduced and as a result of temporal filtering the effect of single outliers is reduced as well.
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