In this paper we detail a preliminary model for reasoning about annotating learning objects and intelligently showing annotations to users who will benefit from them. Student inter...
We propose a novel approach to increase the robustness of object detection algorithms in surveillance scenarios. The cascaded confidence filter successively incorporates constraint...
The current research presents a system that learns to understand object names, spatial relation terms and event descriptions from observing narrated action sequences. The system e...
Development of multiple camera based vision systems for analysis of dynamic objects such as humans is challenging due to occlusions and similarity in the appearance of a person wi...
Abstract. In this paper, we introduce a general and modular framework for formalizing reasoning with incomplete and inconsistent information. Our framework is composed of non-deter...