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» Object Recognition from Large Structural Libraries
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SSPR
2010
Springer
13 years 6 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
ECCV
2010
Springer
14 years 1 months ago
Graph Cut based Inference with Co-occurrence Statistics
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
PAMI
2011
13 years 3 months ago
Bilayer Segmentation of Webcam Videos Using Tree-Based Classifiers
—This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The ...
Pei Yin, Antonio Criminisi, John M. Winn, Irfan A....
NIPS
2000
13 years 9 months ago
The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference
Preliminary work by the authors made use of the so-called "Manhattan world" assumption about the scene statistics of city and indoor scenes. This assumption stated that ...
James M. Coughlan, Alan L. Yuille
PR
2007
109views more  PR 2007»
13 years 7 months ago
Knowledge-based part correspondence
This paper presents a direct method for finding corresponding pairs of parts between two shapes. Statistical knowledge about a large number of parts from many different objects is...
Boaz J. Super