In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Uncertainty estimates related to the position of image features are seeing increasing use in several computer vision problems. Many of these have been recast from standard least s...
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
From the recovery of structure from motion to the separation of style and content, many problems in computer vision have been successfully approached by using bilinear models. The...
We present a practical algorithm that provably achieves the global optimum for a class of bilinear programs commonly arising in computer vision applications. Our approach relies o...