We introduce an approach to accurately detect and segment partially occluded objects in various viewpoints and scales. Our main contribution is a novel framework for combining obj...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Recognition systems have generally treated specular highlights as noise. We show how to use these highlights as a positive source of information that improves recognition of shiny...
Margarita Osadchy, David W. Jacobs, Ravi Ramamoort...
Abstract. Tracking of articulated objects is a challenging task in Computer Vision. A highly target specific model can improve the robustness of the tracking by eliminating or red...
Abstract. An important task in object recognition is to enable algorithms to categorize objects under arbitrary poses in a cluttered 3D world. A recent paper by Savarese & Fei-...