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» Flexible Spatial Models for Grouping Local Image Features
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CVPR
2011
IEEE
12 years 9 months ago
Generalized Group Sparse Classifiers with Application in fMRI Brain Decoding
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Bernard Ng, Rafeef Abugharbieh
ICIP
2008
IEEE
14 years 7 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
DAGM
2009
Springer
14 years 1 days ago
Multi-view Object Detection Based on Spatial Consistency in a Low Dimensional Space
This paper describes a new approach for detecting objects based on measuring the spatial consistency between different parts of an object. These parts are pre-defined on a set of...
Gurman Gill, Martin Levine
CVPR
2004
IEEE
14 years 7 months ago
Spatially Coherent Clustering Using Graph Cuts
Feature space clustering is a popular approach to image segmentation, in which a feature vector of local properties (such as intensity, texture or motion) is computed at each pixe...
Ramin Zabih, Vladimir Kolmogorov
ICPR
2008
IEEE
13 years 12 months ago
Pedestrian detection by modeling local convex shape features
This paper presents a pedestrian model built collectively on a group of strong local convex shape descriptors. The pedestrian model captures the most important features of a pedes...
Jungme Park, Yun Luo, Haoxing Wang, Yi Lu Murphey