We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Motivated by improving statistical shape analysis, this paper presents a novel landmark-based method for accurate shape correspondence, where the general goal is to align multiple...
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
The paper presents a fusion-tracker and pedestrian classifier for color and thermal cameras. The tracker builds a background model as a multi-modal distribution of colors and temp...