Dense height map estimation from oblique aerial image sequences
Computer Vision and Image Understanding
Improving Border Localization of Multi-Baseline Stereo Using Border-Cut
International Journal of Computer Vision
Image and Vision Computing
Trinocular stereo matching with composite disparity space image
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Inpainting in multi-image stereo
Proceedings of the 32nd DAGM conference on Pattern recognition
Disparity map refinement and 3D surface smoothing via directed anisotropic diffusion
Computer Vision and Image Understanding
Towards Unrestrained Depth Inference with Coherent Occlusion Filling
International Journal of Computer Vision
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This paper presents a new model to overcome the occlusion problems coming from wide baseline multiple camera stereo. Rather than explicitly modeling occlusions in the matching cost function, it detects occlusions in the depth map obtained from regular efficient stereo matching algorithms. Occlusions are detected as inconsistencies of the depth map by computing the visibility of the map as it is reprojected into each camera. Our approach has the particularity of not discriminating between occluders and occludees. The matching cost function is modified according to the detected occlusions by removing the offending cameras from the computation of the matching cost. The algorithm gradually modifies the matching cost function according to the history of inconsistencies in the depth map, until convergence. While two graph-theoretic stereo algorithms are used in our experiments, our framework is general enough to be applied to many others. The validity of our framework is demonstrated using real imagery with different baselines.