posted by system || 7594 views || tracked by 17 users: [display]

GREC 2013 : 10th IAPR International Workshop on Graphics Recognition

FacebookTwitterLinkedInGoogle


Conference Series : Graphics Recognition
 
Link: http://grec2013.loria.fr/
 
When Aug 20, 2013 - Aug 21, 2013
Where Bethlehem, PA, USA
Submission Deadline Mar 31, 2013
Categories    pattern recognition   computer graphics
 

Call For Papers

We are pleased to announce that the Tenth IAPR International Workshop on Graphics Recognition (GREC 2013), organized by IAPR TC-10 (Technical Committee on Graphics Recognition), will be held at Lehigh University (Bethlehem, PA, USA) on August 20-21, 2013, just before the 12th International Conference on Document Analysis and Recognition (ICDAR). Transportation shuttle buses will be arranged between GREC and ICDAR.

Since its beginnings the GREC workshops series has provided a unique atmosphere, fostering a very high level of interaction, discussion and exchange of ideas (distinctly different from classical conference-like presentations) while providing high quality and good impact post-proceedings. It therefore froms an excellent opportunity for researchers and practitioners at all levels of experience to meet colleagues and to share new ideas and knowledge about graphics recognition methods. Graphics Recognition is a subfield of document image analysis that deals with graphical entities in written documens, engineering drawings, maps, architectural plans, musical scores, mathematical notation, tables, diagrams, etc.

GREC 2013 will continue the tradition of past workshops held at Penn State University (USA), Nancy (France), Jaipur (India), Kingston (Canada), Barcelona (Spain), Hong Kong (China), Curitiba (Brazil), La Rochelle (France) and Seoul (South Korea).

Workshop Format

The program will be organized in a single-track 2-day workshop. It will comprise several sessions dedicated to specific topics related to graphics in document analysis and graphic recognitio. For each session, there will be an invited presentation describing the state of the art and stating the open questions for the topic of the session, followed by a number of short presentations that will contribute by proposing solutions to some of the questions or presenting results of the speaker's work. Each session will be concluded by a panel discussion.

Topics

Topics of interest include, but are not limited to:

Raster-to-vector techniques.

Recognition of graphical primitives.

Recognition of graphic symbols in charts, diagrams, and drawings.

Interpretation of engineering drawings, maps, tables, and other graphical documents.

Graphics-based information retrieval.

Historical graphic indexing.

3-D models from multiple 2-D views (line drawings).

Identification and localization of graphical mark-ups and annotations in written documents.

Digital ink processing.

Sketch recognition and understanding.

Description of complete systems for interpretation of graphic documents.

Performance evaluation in graphics recognition.

Authoring, editing, storing and presentation systems for graphics multimedia documents.

Related Resources

CVIE 2026   2026 The 4th International Conference on Computer Vision and Information Engineering (CVIE 2026)
RTME 2026   11th International Conference on Recent Trends in Mechanical Engineering
IJCGA 2026   International Journal of Computer Graphics & Animation
IEEE-MLCIPR 2025   2025 2nd International Conference on Machine Learning, Computational Intelligence and Pattern Recognition-EI/Scopus
ICPRAM 2026   15th International Conference on Pattern Recognition Applications and Methods
SNLP 2026   7thInternational Conference on Semantic & Natural Language Processing
Ei/Scopus-CDIVP 2026   2026 6th International Conference on Digital Image and Video Processing (CDIVP 2026)
CVIE--EI 2026   2026 The 4th International Conference on Computer Vision and Information Engineering (CVIE 2026)
PRIA 2025   2025 2nd International Conference on Pattern Recognition and Image Analysis-EI/Scopus
MLSC 2026   7th International Conference on Machine Learning and Soft Computing