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» Gaussian mixture models for probabilistic localization
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170
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CVPR
1999
IEEE
16 years 7 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
ICIP
2008
IEEE
16 years 7 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
IDA
2009
Springer
15 years 10 months ago
Image Source Separation Using Color Channel Dependencies
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Koray Kayabol, Ercan E. Kuruoglu, Bülent Sank...
ESANN
2006
15 years 7 months ago
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM)
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...
Tong Boon Tang, Alan F. Murray
177
Voted
CVPR
2009
IEEE
17 years 28 days ago
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates
We propose a space-time Markov Random Field (MRF) model to detect abnormal activities in video. The nodes in the MRF graph correspond to a grid of local regions in the video fra...
Jaechul Kim (University of Texas at Austin), Krist...