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» A random set formulation for Bayesian SLAM
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TSP
2010
12 years 11 months ago
Joint detection and estimation of multiple objects from image observations
The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as ...
Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Sute...
SAC
2010
ACM
13 years 11 months ago
Tracking random finite objects using 3D-LIDAR in marine environments
This paper presents a random finite set theoretic formulation for multi-object tracking as perceived by a 3D-LIDAR in a dynamic environment. It is mainly concerned with the joint...
Kwang Wee Lee, Bharath Kalyan, W. Sardha Wijesoma,...
IJCV
2008
266views more  IJCV 2008»
13 years 4 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
14 years 12 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)