Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
Abstract. Volume datasets have been a primary representation for scientific visualization with the advent of rendering algorithms such as marching cubes and ray casting. Nonethele...
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Location-based services (LBS) are currently receiving world-wide attention as a consequence of the massive usage of mobile devices, but such location services require scalable dis...
This paper is about a novel rule-based approach for reasoning about qualitative spatiotemporal relations among technology-rich autonomous objects, to which we refer to as artifact...