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» A New Bayesian Framework for Object Recognition
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CVIU
2006
105views more  CVIU 2006»
13 years 7 months ago
The representation and matching of categorical shape
We present a framework for categorical shape recognition. The coarse shape of an object is captured by a multiscale blob decomposition, representing the compact and elongated part...
Ali Shokoufandeh, Lars Bretzner, Diego Macrini, M....
SSPR
2010
Springer
13 years 5 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...
CVPR
2005
IEEE
14 years 9 months ago
Graph Embedding: A General Framework for Dimensionality Reduction
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
Shuicheng Yan, Dong Xu, Benyu Zhang, HongJiang Zha...
ICPR
2008
IEEE
14 years 8 months ago
Joint visual vocabulary for animal classification
This paper presents a method for visual object categorization based on encoding the joint textural information in objects and the surrounding background, and requiring no segmenta...
Alireza Tavakoli Targhi, Andrzej Pronobis, Heydar ...
CVPR
2007
IEEE
14 years 9 months ago
Layered Graph Match with Graph Editing
Many vision tasks are posed as either graph partitioning (coloring) or graph matching (correspondence) problems. The former include segmentation and grouping, and the latter inclu...
Liang Lin, Song Chun Zhu, Yongtian Wang