Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
The usefulness of ontology is strongly dependent on the knowledge representation policy and its maintenance. The subject of knowledge representation and modeling tool has been one...
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
We propose a novel approach to understanding
activities from their partial observations monitored through
multiple non-overlapping cameras separated by unknown time
gaps. In our...