Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors
Identifieur interne : 000C26 ( Main/Exploration ); précédent : 000C25; suivant : 000C27Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors
Auteurs : Thanh Ha Do [France] ; Salvatore Tabbone [France] ; Oriol Ramos Terrades [Espagne]Source :
English descriptors
Abstract
This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising.
Url:
DOI: 10.1109/DAS.2014.62
Affiliations:
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More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising.</div></front></TEI><affiliations><list><country><li>Espagne</li><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Do, Thanh Ha" sort="Do, Thanh Ha" uniqKey="Do T" first="Thanh Ha" last="Do">Thanh Ha Do</name></region><name sortKey="Tabbone, Salvatore" sort="Tabbone, Salvatore" uniqKey="Tabbone S" first="Salvatore" last="Tabbone">Salvatore Tabbone</name></country><country name="Espagne"><noRegion><name sortKey="Ramos Terrades, Oriol" sort="Ramos Terrades, Oriol" uniqKey="Ramos Terrades O" first="Oriol" last="Ramos Terrades">Oriol Ramos Terrades</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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