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CVPR
2008
IEEE
16 years 9 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
IPMI
2003
Springer
16 years 8 months ago
Expectation Maximization Strategies for Multi-atlas Multi-label Segmentation
It is well-known in the pattern recognition community that the accuracy of classifications obtained by combining decisions made by independent classifiers can be substantially high...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
TSP
2010
15 years 2 months ago
Optimization and analysis of distributed averaging with short node memory
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
ICCV
2009
IEEE
17 years 17 days ago
Mode-Detection via Median-Shift
Median-shift is a mode seeking algorithm that relies on computing the median of local neighborhoods, instead of the mean. We further combine median-shift with Locality Sensitive...
Lior Shapira, Shai Avidan, Ariel Shamir
CVPR
2003
IEEE
16 years 9 months ago
Joint 3D-Reconstruction and Background Separation in Multiple Views using Graph Cuts
This paper deals with simultaneous depth map estimation and background separation in a multi-view setting with several fixed calibrated cameras, two problems which have previously...
Bastian Goldlücke, Marcus A. Magnor