We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
—SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition...
Christoph Strecha, Alexander A. Bronstein, Michael...
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Computational photography combines plentiful computing, digital sensors, modern optics, actuators, and smart lights to escape the limitations of traditional cameras, enables novel ...
In some applications objects are known to have nonsmooth or “jagged” edges, which are not well approximated by smooth curves. We use subdivision curves as a simple but flexib...