Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Abstract—Segmentation of architectural floorplans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional...
Markov random field (MRF, CRF) models are popular in
computer vision. However, in order to be computationally
tractable they are limited to incorporate only local interactions
a...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...
Human activity analysis is an important problem in computer
vision with applications in surveillance and summarization
and indexing of consumer content. Complex human
activities...