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Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks

15 Aug
Thursday, 08/15/2013 11:00am to 12:00pm
Seminar

Simone Marinai
University of Florence
Computer Engineering at the Information Engineering Department

Computer Science Building, Room 151

Faculty Host: R. Manmatha

Natural languages can often be modeled by suitable grammars whose knowledge can improve the word spotting results.  The implicit contextual information is even more useful when dealing with information that is intrinsically described  as one collection of records.  In this talk, we present one approach to word spotting which uses the contextual information of records to improve  the results.  The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records.  The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.

Bio:Simone Marinai received the Master Degree in Electronic Engineering in 1992 and the PhD Degree in Computer Engineering in 1996 both from the University of Florence, Italy.  In 1996 he has been visiting researcher at CENPARMI, Concordia University, Montreal.  Currently he is Associate Professor of Computer Engineering at the Information Engineering department of  the University of Florence.

His main research interests are in Artificial Intelligence and Pattern Recognition with a special focus on applications in Document Engineering and Document Image Analysis.  Prof. Marinai is editor in chief of the International Journal on Document Analysis and Recognition (IJDAR) and of the Electronic Letters on Computer Vision and Image Analysis (ELCVIA) journal; Chair of the Conferences and Meetings (C&M) committee of IAPR; Past chair of the  IAPR Technical Committee on Neural Networks and Computational Intelligence (TC3); Advisory board member of ICDAR; Publicity  Co-Chair for ICDAR 2009; Tutorial Chair for ICDAR 2013; Co-chair of DAS 2004, ANNPR 2003, ANNPR 2006, ANNPR 2008, NNLDAR 2005, DAUDD 1999; Symposium Chair of DocEng 2013 and Program Chair of ICFHR 2016; area chair of ICPR 2010, 2012 and 2014; He is co-editor of the book "Machine Learning in Document Analysis and Recognition" published by Springer Verlag in 2008.  He is author of more than 60 peer-reviewed publications and editor of four volumes.