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» Modeling Redundancy: Quantitative and Qualitative Models
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ECCV
2008
Springer
14 years 11 months ago
Segmentation and Recognition Using Structure from Motion Point Clouds
We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3...
Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur...
ECCV
2004
Springer
14 years 11 months ago
An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets
Abstract. We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or be...
Zia Khan, Tucker R. Balch, Frank Dellaert
IPMI
2005
Springer
14 years 10 months ago
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images
Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain ...
Alan S. Willsky, Godtfred Holmvang, Müjdat &C...
ICDCS
2005
IEEE
14 years 2 months ago
Comparison of Approaches to Service Deployment
IT today is driven by the trend of increasing scale and complexity. Utility and Grid computing models, PlanetLab, and traditional data centers, are reaching the scale of thousands...
Vanish Talwar, Qinyi Wu, Calton Pu, Wenchang Yan, ...
GECCO
2004
Springer
175views Optimization» more  GECCO 2004»
14 years 2 months ago
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, ...