This paper presents a novel approach to recovering temporally coherent estimates of 3D structure of a dynamic scene from a sequence of binocular stereo images. The approach is bas...
Abstract. Visual dictionary learning and base (binary) classifier training are two basic problems for the recently most popular image categorization framework, which is based on t...
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
The dictionary approach to signal and image processing has been massively investigated in the last two decades, proving very attractive for a wide range of applications. The effec...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...