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» LASIC: A model invariant framework for correspondence
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ICIP
2008
IEEE
14 years 6 months ago
LASIC: A model invariant framework for correspondence
In this paper we address two closely related problems. The first is the object detection problem, i.e., the automatic decision of whether a given image represents a known object o...
Bernardo Rodrigues Pires, João Xavier, Jos&...
ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
14 years 9 months ago
Feature Correspondence and Deformable Object Matching via Agglomerative Correspondence Clustering
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local ...
Minsu Cho (Seoul National University), Jungmin Lee...
ECCV
2010
Springer
13 years 3 months ago
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition
We present a novel framework for the recognition of facial expressions at arbitrary poses that is based on 2D geometric features. We address the problem by first mapping the 2D loc...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
MICCAI
1998
Springer
13 years 9 months ago
Multi-object Deformable Templates Dedicated to the Segmentation of Brain Deep Structures
We propose a new way of embedding shape distributions in a topological deformable template. These distributions rely on global shape descriptors corresponding to the 3D moment inva...
Fabrice Poupon, Jean-Francois Mangin, Dominique Ha...
ICCV
2009
IEEE
13 years 2 months ago
SURF Tracking
Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motionbased trackin...
Wei He, Takayoshi Yamashita, Hongtao Lu, Shihong L...