Temporal selection of images for a fast algorithm for depth-map extraction in multi-baseline configurations

Obtaining accurate depth maps from multi-view configurations is an essential component for dense scene reconstruction from images and videos. In the first part of this paper, a plane sweep algorithm for sampling an energy function for every depth label and a dense set of points is presented. The distinctive features of this algorithm are 1) that despite a flexible model choice for the underlying geometry and radiometry, the energy function is performed by merely image operations instead of pixel-wise computations, and 2) that it can be easily manipulated by different terms, such as triangle-based smoothing term, or post-processed by one of the numerous state-of-the-art non-local energy minimization algorithms. The second contribution of this paper is a search for optimal ways to aggregate multiple observations in order to make the cost function more robust near the image border and in occlusions areas. Experiments with different data sets show the relevance of the proposed research, emphasize the potential of the algorithm, and provide ideas of future work.