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TIP
2008
169views more  TIP 2008»
13 years 6 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
FOSSACS
2005
Springer
14 years 3 days ago
Branching Cells as Local States for Event Structures and Nets: Probabilistic Applications
We study the concept of choice for true concurrency models such as prime event structures and safe Petri nets. We propose a dynamic variation of the notion of cluster previously in...
Samy Abbes, Albert Benveniste
BC
2008
134views more  BC 2008»
13 years 6 months ago
Interacting with an artificial partner: modeling the role of emotional aspects
In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated a...
Isabella Cattinelli, Massimiliano Goldwurm, N. Alb...
ICRA
2007
IEEE
160views Robotics» more  ICRA 2007»
14 years 27 days ago
CRF-Filters: Discriminative Particle Filters for Sequential State Estimation
Abstract— Particle filters have been applied with great success to various state estimation problems in robotics. However, particle filters often require extensive parameter tw...
Benson Limketkai, Dieter Fox, Lin Liao
ICPR
2000
IEEE
14 years 7 months ago
Image Distance Using Hidden Markov Models
We describe a method for learning statistical models of images using a second-order hidden Markov mesh model. First, an image can be segmented in a way that best matches its stati...
Daniel DeMenthon, David S. Doermann, Marc Vuilleum...