SymPaD: Symbolic patch descriptor
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Date
2015
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SciTePress
Open Access Color
HYBRID
Green Open Access
No
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Abstract
We propose a new local image descriptor named SymPaD for image understanding. SymPaD is a probability vector associated with a given image pixel and represents the attachment of the pixel to a previously designed shape repertoire. As such the approach is model-driven. The SymPad descriptor is illumination and rotation invariant, and extremely flexible on extending the repertoire with any parametrically generated geometrical shapes and any desired additional transformation types. Copyright © 2015 SCITEPRESS - Science and Technology Publications All rights reserved.
Description
Institute for Systems and Technologies of Information, Control and Communication (INSTICC)
10th International Conference on Computer Vision Theory and Applications, VISAPP 2015 -- 11 March 2015 through 14 March 2015 -- 112690
10th International Conference on Computer Vision Theory and Applications, VISAPP 2015 -- 11 March 2015 through 14 March 2015 -- 112690
Keywords
Image feature, Image understanding, Model-driven visual dictionary, Object recognition, Primitive structures of natural images, Image understanding, Mathematical transformations, Object recognition, Geometrical shapes, Image features, Local image descriptors, Natural images, Probability vector, Rotation invariant, Transformation types, Visual dictionaries, Pixels, Image understanding, Image feature, Model-driven visual dictionary, Object recognition, Primitive structures of natural images, Image feature; Image understanding; Model-driven visual dictionary; Object recognition; Primitive structures of natural images
Fields of Science
03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
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1
Source
VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; VISIGRAPP, Proceedings
Volume
1
Issue
Start Page
266
End Page
271
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CrossRef : 1
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