Sciweavers

126 search results - page 18 / 26
» Discriminative Random Fields for Behavior Modeling
Sort
View
ECCV
2000
Springer
14 years 10 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...
ICASSP
2010
IEEE
13 years 8 months ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
CVIU
2006
222views more  CVIU 2006»
13 years 8 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
SIGMETRICS
2009
ACM
182views Hardware» more  SIGMETRICS 2009»
14 years 3 months ago
The age of gossip: spatial mean field regime
Disseminating a piece of information, or updates for a piece of information, has been shown to benefit greatly from simple randomized procedures, sometimes referred to as gossipi...
Augustin Chaintreau, Jean-Yves Le Boudec, Nikodin ...
AAAI
2000
13 years 10 months ago
Modeling Classification and Inference Learning
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...