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CBDAR 2017 : 7th International Workshop on Camera Based Document Analysis and Recognition

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Conference Series : Camera-Based Document Analysis and Recognition
 
Link: http://www.cvc.uab.es/cbdar2017/?c=home
 
When Nov 11, 2017 - Nov 11, 2017
Where Kyoto, Japan
Submission Deadline Jul 15, 2017
Notification Due Aug 10, 2017
Final Version Due Sep 1, 2017
Categories    computer science   pattern recognition   document image analysis   camera-based document analysis
 

Call For Papers

The pervasiveness and widespread availability of camera phones, hand-held digital still/video cameras and more recently wearable cameras have led the community to recognize camera captured images as a promising and growing field of research for document analysis and recognition. Document digitization techniques are gradually getting closer to camera based solutions, offering certain advantages (e.g. for scanning large scale or fragile documents), and presenting interesting new challenges and open problems which cannot be directly resolved by traditional techniques.

Building on the success of the previous six CBDAR workshops in 2005 (Seoul, Korea), 2007 (Curitiba, Brazil), 2009 (Barcelona, Spain), 2011 (Beijing, China), 2013 (Washington DC, USA), and 2015 (Nancy, France), CBDAR 2017 will be held in Kyoto, Japan in conjunction with ICDAR 2017. The aim of the workshop is to provide a natural link between document image analysis and the wider computer vision community by attracting cutting edge research on the topic.


Topics of Interest

Camera based acquisition of written information
Restoration of camera captured documents (dewarping, deblurring, etc.)
Camera-based document analysis and recognition
Document image quality assessment / estimation
Image degradation models for camera captured characters/documents
Text extraction from scene images
Text in video
Document image retrieval
Device constrained techniques and algorithms
Performance evaluation and metrics
Mobile OCR
Smartphone-based document scanning
Applications
Feature extraction in camera capture situations

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