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Sobre

Sobre

Sou Mestre em Engenharia Informática e Computação, tendo frequentado o curso que antes do processo de Bolonha era designado por LEIC (Licenciatura em Engenharia Informática e Computação), no qual ingressei, na Faculdade de Engenharia da Universidade do Porto (FEUP), em 2001. No ano letivo de 2006/2007 tive o meu primeiro contacto com o INESC, no 2º semestre, através do estágio de fim de curso, na antiga UTM, sob orientação do Prof. Jaime Cardoso. No ano de 2007 decorreu a transição do curso LEIC para MIEIC (Mestrado Integrado em Engenharia Informática e Computação), na FEUP, e foi dada a possibilidade aos alunos para concluírem o curso como LEIC ou continuarem como MIEIC. Pensando no meu futuro optei por continuar no novo curso, realizando a respetiva dissertação, sob a mesma orientação no INESC, tendo concluído em 2008 com o grau de Mestre.

Fui bolseiro no ano de 2008 e em 2009 não estive associado ao INESC, mas em Dezembro desse ano regressei, mas numa outra unidade, a antiga USIG, agora designada por CSIG, sob orientação do Engº José Correia, na qual permaneço até à atualidade.

No meu percurso no INESC Porto - agora INESC TEC -, participei em vários projetos e atividades de diferentes âmbitos e objetivos, desde investigação a prestação de serviços, nomeadamente com a realização de desenvolvimento e participação em projetos de consultoria, tendo inclusive adquirido ao longo deste percurso novos conhecimentos e capacidades que fortaleceram as minhas competências. Nos trabalhos de investigação houve publicação de artigos científicos e participação em conferências.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Guilherme Artur Capela
  • Cargo

    Investigador
  • Desde

    15 fevereiro 2007
019
Publicações

2010

Optical recognition of music symbols

Autores
Rebelo, A; Capela, G; Cardoso, JS;

Publicação
INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION

Abstract
Many musical works produced in the past are still currently available only as original manuscripts or as photocopies. The preservation of these works requires their digitalization and transformation into a machine-readable format. However, and despite the many research activities on optical music recognition (OMR), the results for handwritten musical scores are far from ideal. Each of the proposed methods lays the emphasis on different properties and therefore makes it difficult to evaluate the efficiency of a proposed method. We present in this article a comparative study of several recognition algorithms of music symbols. After a review of the most common procedures used in this context, their respective performances are compared using both real and synthetic scores. The database of scores was augmented with replicas of the existing patterns, transformed according to an elastic deformation technique. Such transformations aim to introduce invariances in the prediction with respect to the known variability in the symbols, particularly relevant on handwritten works. The following study and the adopted databases can constitute a reference scheme for any researcher who wants to confront a new OMR algorithm face to well-known ones.

2009

Staff Detection with Stable Paths

Autores
Cardoso, JD; Capela, A; Rebelo, A; Guedes, C; da Costa, JP;

Publicação
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Abstract
The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms.

2008

A CONNECTED PATH APPROACH FOR STAFF DETECTION ON A MUSIC SCORE

Autores
Cardoso, JS; Capela, A; Rebelo, A; Guedes, C;

Publicação
2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5

Abstract
The preservation of many music works produced in the past entails their digitalization and consequent accessibility in an easy-to-manage digital format. Carrying this task manually is very time consuming and error prone. While optical music recognition systems usually perform well on printed scores, the processing of handwritten musical scores by computers remain far from ideal. One of the fundamental stages to carry out this task is the staff line detection. In this paper a new method for the automatic detection of music staff lines based on a connected path approach is presented. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms.

2008

Integrated Recognition System for Music Scores

Autores
Capela, A; Cardoso, JS; Rebelo, A; Guedes, C;

Publicação
Proceedings of the 2008 International Computer Music Conference, ICMC 2008, Belfast, Ireland, August 24-29, 2008

Abstract
Many music works produced in the last century still exist only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a digital format easy-to-manage which encourages browsing, retrieval, search and analysis while providing a generalized access to the digital material. The manual process to carry out this task is very time consuming and error prone. Automatic optical music recognition (OMR) has emerged as a partial solution to this problem. However, the full potential of this process only reveals itself when integrated in a system that provides seamless access to browsing, retrieval, search and analysis. We address this demand by proposing a modular, flexible and scalable framework that fully integrates the abovementioned functionalities. A web based system to carry out the automatic recognition process, allowing the creation and management of a music corpus, while providing generalized access to it, is a unique and innovative approach to the problem. A prototype has been implemented and is being used as a test platform for OMR algorithms.

2008

Staff line detection and removal with stable paths

Autores
Capela, A; Rebelo, A; Cardoso, JS; Guedes, C;

Publicação
SIGMAP 2008: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATIONS

Abstract
Many music works produced in the past are currently available only as original manuscripts or as photocopies. Preserving them entails their digitalization and consequent accessibility in a machine-readable format, which encourages browsing, retrieval, search and analysis while providing a generalized access to the digital material. Carrying this task manually is very time consuming and error prone. While optical music recognition (OMR) systems usually perform well on printed scores, the processing of handwritten music by computers remains below the expectations. One of the fundamental stages to carry out this task is the detection and subsequent removal of staff lines. In this paper we integrate a general-purpose, knowledge-free method for the automatic detection of staff lines based on stable paths, into a recently developed staff line removal toolkit. Lines affected by curvature, discontinuities, and inclination are robustly detected. We have also developed a staff removal algorithm adapting an existing line removal approach to use the stable path algorithm at the detection stage, Experimental results show that the proposed technique outperforms well-established algorithms. The developed algorithm will now be integrated in a web based system providing seamless access to browsing, retrieval, search and analysis of submitted scores.