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IJCV
2006
161views more  IJCV 2006»
13 years 10 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
AUTOMATICA
2006
87views more  AUTOMATICA 2006»
13 years 10 months ago
Modeling continuous-time processes via input-to-state filters
A direct algorithm to estimate continuous-time ARMA (CARMA) models is proposed in this paper. In this approach, we first pass the observed data through an input-to-state filter an...
Kaushik Mahata, Minyue Fu
NIPS
2003
14 years 3 days ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
GI
2009
Springer
14 years 3 months ago
Self-monitoring for Computer Users
: We are presenting a tool for collecting and analysing computer usage data. The observed data are locally used by the user to self-monitor and self-reflect her behaviour, decontro...
Maren Scheffel, Martin Friedrich, Marco Jahn, Uwe ...
AUSAI
2009
Springer
14 years 5 months ago
Enhancing MML Clustering Using Context Data with Climate Applications
Abstract. In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data ite...
Gerhard Visser, David L. Dowe, Petteri Uotila
ICRA
2009
IEEE
144views Robotics» more  ICRA 2009»
14 years 5 months ago
Clothes state recognition using 3D observed data
Abstract— In this paper, we propose a deformable-modeldriven method to recognize the state of hanging clothes using three-dimensional (3D) observed data. For the task to pick up ...
Yasuyo Kita, Toshio Ueshiba, Ee Sian Neo, Nobuyuki...
ICCV
2005
IEEE
15 years 20 days ago
Detecting Irregularities in Images and in Video
We address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. The term &qu...
Oren Boiman, Michal Irani