In this paper, we propose a new algorithm for the fundamental problem of reconstructing surfaces from a large set of unorganized 3D data points. The local shapes of the surface ar...
Abstract—We propose a method for the reconstruction of signals and images observed partially through a linear operator with a large support (e.g., a Fourier transform on a sparse...
This paper addresses variational supervised texture segmentation. The main contributions are twofold. First, the proposed method circumvents a major problem related to classical t...
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...