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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Primitive Segmentation in Old Handwritten Music Scores |
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2005 |
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6th IAPR International Workshop on Graphics Recognition (GREC 2005) |
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Hong Kong, Hong Kong SAR (China) |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Staff and graphical primitive segmentation in old handwritten music scores |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Primitive Segmentation in Old Handwritten Music Scores |
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2006 |
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Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 288–299 |
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DAG @ dag @ FLS2006 |
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697 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Old Handwritten Musical Symbol Classification by a Dynamic Time Warping Based Method |
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2007 |
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Seventh IAPR International Workshop on Graphics Recognition |
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26–27 |
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Curitiba (Brazil) |
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GREC |
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DAG @ dag @ FLS2007 |
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887 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados; Gemma Sanchez |
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Title |
Old Handwritten Musical Symbol Classification by a Dynamic TimeWrapping Based Method |
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2008 |
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Graphics Recognition: Recent Advances and New Opportunities |
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5046 |
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52–60 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG @ dag @ FLS2008a |
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990 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Josep Llados |
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Title |
A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores |
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2010 |
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12th International Conference on Frontiers in Handwriting Recognition |
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634 - 639 |
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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates. |
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Kolkata (India) |
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978-1-4244-8353-2 |
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ICFHR |
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DAG @ dag @ FoL2010 |
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1321 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Gemma Sanchez |
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Title |
Analysis and Recognition of Music Scores |
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2014 |
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Handbook of Document Image Processing and Recognition |
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749-774 |
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The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-860-7 |
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DAG; ADAS; 600.076; 600.077 |
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Admin @ si @ FoS2014 |
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2484 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Beata Megyesi; Joan Mas |
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Title |
Transcription of Encoded Manuscripts with Image Processing Techniques |
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2017 |
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Digital Humanities Conference |
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441-443 |
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DAG; 600.097; 600.121 |
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Admin @ si @ FMM2017 |
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3061 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Bart Lamiroy |
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Title |
Graphics Recognition, Current Trends and Evolutions |
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2018 |
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Graphics Recognition, Current Trends and Evolutions |
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11009 |
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This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
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Springer International Publishing |
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978-3-030-02283-9 |
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DAG; 600.121 |
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Admin @ si @ FoL2018 |
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3171 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Alicia Fornes; Asma Bensalah; Cristina Carmona_Duarte; Jialuo Chen; Miguel A. Ferrer; Andreas Fischer; Josep Llados; Cristina Martin; Eloy Opisso; Rejean Plamondon; Anna Scius-Bertrand; Josep Maria Tormos |
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Title |
The RPM3D Project: 3D Kinematics for Remote Patient Monitoring |
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Conference Article |
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2022 |
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Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 |
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13424 |
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217-226 |
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Healthcare applications; Kinematic; Theory of Rapid Human Movements; Human activity recognition; Stroke rehabilitation; 3D kinematics |
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This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of Rapid Human Movement. We have validated our research in a real case scenario for stroke rehabilitation at the Guttmann Institute (https://www.guttmann.com/en/) (neurorehabilitation hospital), showing promising results. Our work could have a great impact in remote healthcare applications, improving the medical efficiency and reducing the healthcare costs. Future steps include more clinical validation, developing multi-modal analysis architectures (analysing data from sensors, images, audio, etc.), and exploring the application of our technology to monitor other neurodegenerative diseases. |
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June 7-9, 2022, Las Palmas de Gran Canaria, Spain |
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IGS |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ FBC2022 |
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3739 |
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