Original paper
Sparse representation over learned dictionary for symbol recognition
Abstract
In this paper we propose an original sparse vector model for symbol retrieval task. More specifically, we apply the K-SVD algorithm for learning a visual dictionary based on symbol descriptors locally computed around interest points. Results on benchmark datasets show that the obtained sparse representation is competitive related to state-of-the-art methods. Moreover, our sparse representation is invariant to rotation and scale transforms and...
Paper Details
Title
Sparse representation over learned dictionary for symbol recognition
Published Date
Aug 1, 2016
Journal
Volume
125
Pages
36 - 47
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Notes
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