Efficient, Precise, and Accurate Utilization of the Uniqueness Constraint in Multi-View Stereo

In this paper, the depth cue due to the assumption of texture uniqueness is reviewed. The spatial direction over which a similarity measure is optimized, in order to establish a stereo correspondence, is considered and methods to increase the precision and accuracy of stereo reconstructions are presented. An efficient implementation of the above methods is offered, based on optimizations that evaluate potential correspondences hierarchically, in the spatial and angular dimensions. Furthermore, the expansion of the above techniques in a multi-view framework where calibration errors cause the misregistration of individually obtained reconstructions are considered, and a treatment of the data is proposed for the elimination of duplicate reconstructions of a single surface point. Finally, a processing step is proposed for the increase of reconstruction precision and post-processing of the final result. The above contributions are integrated in a generic and parallelizable implementation of the uniqueness constraint to observe speedup and increase in the fidelity of surface reconstruction.