Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
This paper presents a novel approach for online subspace learning based on an incremental version of the nonparametric discriminant analysis (NDA). For many real-world applications...
—As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective ...
Shape information is utilized by numerous applications in computer vision, scientific visualization and computer graphics. This paper presents a novel algorithm for exploring and ...
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...