We present an algorithm for clustering sets of detected
interest points into groups that correspond to visually dis-
tinct structure. Through the use of a suitable colour and tex...
Finding correspondences between feature points is one
of the most relevant problems in the whole set of visual
tasks. In this paper we address the problem of matching
a feature ...
In this paper, we introduce a new approach for modeling
visual context. For this purpose, we consider the leaves of a
hierarchical segmentation tree as elementary units. Each
le...
Joseph J. Lim, Pablo Arbelaez, Chunhui Gu, and Jit...
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
Can we detect low dimensional structure in high dimensional data sets of images? In this paper, we propose an algorithm for unsupervised learning of image manifolds by semidefinit...