Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Abstract. In this paper we present our work on markerless model-based 3D human motion capture using multiple cameras. We use an industry proven anthropometric human model that was ...
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...