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» Context and Hierarchy in a Probabilistic Image Model
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ISMIS
1997
Springer
13 years 11 months ago
Knowledge-Based Image Retrieval with Spatial and Temporal Constructs
e about image features can be expressed as a hierarchical structure called a Type Abstraction Hierarchy (TAH). TAHs can be generated automatically by clustering algorithms based on...
Wesley W. Chu, Alfonso F. Cardenas, Ricky K. Taira
PAMI
2010
205views more  PAMI 2010»
13 years 5 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
ICCV
2005
IEEE
14 years 9 months ago
Detecting Irregularities in Images and in Video
We address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. The term &qu...
Oren Boiman, Michal Irani
CVPR
2009
IEEE
15 years 2 months ago
Contextual Restoration of Severely Degraded Document Images
We propose an approach to restore severely degraded document images using a probabilistic context model. Un- like traditional approaches that use previously learned prior models...
Jyotirmoy Banerjee, Anoop M. Namboodiri, C. V. Jaw...
TMM
2002
104views more  TMM 2002»
13 years 7 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...