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» Object Recognition Using Segmentation for Feature Detection
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ECCV
2008
Springer
16 years 3 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
PAMI
2000
113views more  PAMI 2000»
15 years 1 months ago
Hierarchical Discriminant Regression
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
Wey-Shiuan Hwang, Juyang Weng
TITB
2008
97views more  TITB 2008»
15 years 1 months ago
A Novel Breast Tissue Density Classification Methodology
Abstract--It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastic...
Arnau Oliver, Jordi Freixenet, Robert Marti, Josep...

Book
5396views
17 years 27 days ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
ICAPR
2009
Springer
15 years 8 months ago
Distraction Free Evolution of Active Contours
We propose a novel energy term to make the curve evolution quite robust to spurious edges. The physical intuition behind the formulation is that an object edge is generally contin...
Viswanathan Srikrishnan, Subhasis Chaudhuri