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CVPR
2008
IEEE
16 years 8 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 ...
CVPR
2008
IEEE
16 years 8 months ago
Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...
Diana Mateus, Radu Horaud, David Knossow, Fabio Cu...
217
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ECCV
2008
Springer
16 years 8 months ago
Learning Visual Shape Lexicon for Document Image Content Recognition
Developing effective content recognition methods for diverse imagery continues to challenge computer vision researchers. We present a new approach for document image content catego...
Guangyu Zhu, Xiaodong Yu, Yi Li, David S. Doermann
ECCV
2004
Springer
16 years 8 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
ECCV
2006
Springer
16 years 8 months ago
A Theory of Spherical Harmonic Identities for BRDF/Lighting Transfer and Image Consistency
Abstract. We develop new mathematical results based on the spherical harmonic convolution framework for reflection from a curved surface. We derive novel identities, which are the ...
Dhruv Mahajan, Ravi Ramamoorthi, Brian Curless