An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
This paper shows how semantic attribute features can be used to improve object classification performance. The semantic attributes used fall into five groups: scene (e.g. `road...
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
We present a patch-based algorithm for the purpose of object classification in video surveillance. Within detected regions-of-interest (ROIs) of moving objects in the scene, a feat...