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 describes a machine learning approach for visual
object detection which is capable of processing images
extremely rapidly and achieving high detection rates. This
wor...
Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during t...
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...