Consensus-based multiview texturing and depth-map completion
We describe an active depth imaging system based on phase measuring triangulation. Typically depth-maps generated with such 3D scanning systems suffer from occlusions and imperfections, especially in the vicinity of depth discontinuities. Applying multiple color images, captured with a camera array, for view synthesis from the erroneous depth-maps can result in severe texturing artifacts. Our consensus-based approach greatly reduces these artifacts by comparing the similarity of the multiview texture images during the blending process to detect outliers in the form of foreground texture projected on background surfaces and specular ambiguity. Additionally, the approach is applied to dramatically improve the depth-maps by generating multiple depth-map hypotheses and selecting the areas of each that have the highest consensus with the set of multiview texture images. Our approach yields accurate and occlusion-free depth-maps in real-time.