View source for Publications/chazalon.17.icdar-ost

{{Publication
| published = true
| date = 2017-07-21
| title = SmartDoc 2017 Video Capture: Mobile Document Acquisition in Video Mode
| authors = J Chazalon, P Gomez-Krämer, J -C Burie, M Coustaty, S Eskenazi, M Luqman, N Nayef, M Rusiñol, N Sidère, J M Ogier.
| booktitle = Proceedings of the 1st International Workshop on Open Services and Tools for Document Analysis (ICDAR-OST)
| pages = 11 to 16
| address = Kyoto, Japan
| abstract = As mobile document acquisition using smartphones is getting more and more common, along with the continuous improvement of mobile devices (both in terms of computing power and image quality), we can wonder to which extent mobile phones can replace desktop scanners. Modern applications can cope with perspective distortion and normalize the contrast of a document page captured with a smartphone, and in some cases like bottle labels or posters, smartphones even have the advantage of allowing the acquisition of non-flat or large documents. Howeverseveral cases remain hard to handle, such as reflective documents (identity cards, badges, glossy magazine coveretc.) or large documents for which some regions require an important amount of detail. This paper introduces the SmartDoc 2017 benchmark (named “SmartDoc Video Capture”)which aims at assessing whether capturing documents using the video mode of a smartphone could solve those issues. The task under evaluation is both a stitching and a reconstruction problem, as the user can move the device over different parts of the document to capture details or try to erase highlights. The material released consists of a dataset, an evaluation method and the associated tool, a sample method, and the tools required to extend the dataset. All the components are released publicly under very permissive licenses, and we particularly cared about maximizing the ease of understanding, usage and improvement.
| lrdepaper = http://www.lrde.epita.fr/dload/papers/chazalon.17.icdar-ost.pdf
| lrdeprojects = Olena
| lrdekeywords = Image
| lrdenewsdate = 2017-07-21
| type = inproceedings
| id = chazalon.17.icdar-ost
| identifier = doi:10.1109/ICDAR.2017.306
| bibtex = 
@InProceedings<nowiki>{</nowiki>	  chazalon.17.icdar-ost,
  title		= <nowiki>{</nowiki><nowiki>{</nowiki>SmartDoc<nowiki>}</nowiki> 2017 Video Capture: <nowiki>{</nowiki>M<nowiki>}</nowiki>obile Document
		  Acquisition in Video Mode<nowiki>}</nowiki>,
  author	= <nowiki>{</nowiki>J. Chazalon and P. Gomez-Kr<nowiki>{</nowiki>\"a<nowiki>}</nowiki>mer and J.-C. Burie and M.
		  Coustaty and S. Eskenazi and M. Luqman and N. Nayef and M.
		  Rusi<nowiki>{</nowiki>\~n<nowiki>}</nowiki>ol and N. Sid<nowiki>{</nowiki>\`e<nowiki>}</nowiki>re and J.M. Ogier.<nowiki>}</nowiki>,
  booktitle	= <nowiki>{</nowiki>Proceedings of the 1st International Workshop on Open
		  Services and Tools for Document Analysis (ICDAR-OST)<nowiki>}</nowiki>,
  year		= <nowiki>{</nowiki>2017<nowiki>}</nowiki>,
  month		= nov,
  pages		= <nowiki>{</nowiki>11--16<nowiki>}</nowiki>,
  address	= <nowiki>{</nowiki>Kyoto, Japan<nowiki>}</nowiki>,
  abstract	= <nowiki>{</nowiki>As mobile document acquisition using smartphones is
		  getting more and more common, along with the continuous
		  improvement of mobile devices (both in terms of computing
		  power and image quality), we can wonder to which extent
		  mobile phones can replace desktop scanners. Modern
		  applications can cope with perspective distortion and
		  normalize the contrast of a document page captured with a
		  smartphone, and in some cases like bottle labels or
		  posters, smartphones even have the advantage of allowing
		  the acquisition of non-flat or large documents. However,
		  several cases remain hard to handle, such as reflective
		  documents (identity cards, badges, glossy magazine cover,
		  etc.) or large documents for which some regions require an
		  important amount of detail. This paper introduces the
		  SmartDoc 2017 benchmark (named ``SmartDoc Video Capture''),
		  which aims at assessing whether capturing documents using
		  the video mode of a smartphone could solve those issues.
		  The task under evaluation is both a stitching and a
		  reconstruction problem, as the user can move the device
		  over different parts of the document to capture details or
		  try to erase highlights. The material released consists of
		  a dataset, an evaluation method and the associated tool, a
		  sample method, and the tools required to extend the
		  dataset. All the components are released publicly under
		  very permissive licenses, and we particularly cared about
		  maximizing the ease of understanding, usage and
		  improvement.<nowiki>}</nowiki>,
  doi		= <nowiki>{</nowiki>10.1109/ICDAR.2017.306<nowiki>}</nowiki>
<nowiki>}</nowiki>

}}