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Use of a Large Image Repository to Enhance Domain Dataset for Flyer Classification

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Book cover Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9475))

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Abstract

This paper describes our exploratory work on supplementing our dataset of images extracted from real estate flyers with images from a large general image repository to enhance the breadth of the samples and create a classification model which would perform well for totally unseen, new instances. We selected some images from the Scene UNderstanding (SUN) database which are annotated with the scene categories that seem to match with our flyer images, and added them to our flyer dataset. We ran a series of experiments with various configurations of flyer vs. SUN data mix. The results showed that the classification models trained with a mixture of SUN and flyer images produced comparable accuracies as the models trained solely with flyer images. This suggests that we were able to create a model which is scalable to unseen, new data without sacrificing the accuracy of the data at hand.

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Notes

  1. 1.

    http://groups.csail.mit.edu/vision/SUN/.

  2. 2.

    We used pdf to html (http://sourceforge.net/projects/pdftohtml/) to convert pdf to html, and Gimp (http://www.gimp.org/) to crop individual images.

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Authors and Affiliations

  1. DePaul University, 243 S. Wabash Ave, Chicago, IL, 60604, USA

    Payam Pourashraf & Noriko Tomuro

Authors
  1. Payam Pourashraf
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  2. Noriko Tomuro
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Corresponding author

Correspondence to Payam Pourashraf .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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© 2015 Springer International Publishing Switzerland

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Pourashraf, P., Tomuro, N. (2015). Use of a Large Image Repository to Enhance Domain Dataset for Flyer Classification. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_56

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  • DOI: https://doi.org/10.1007/978-3-319-27863-6_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27862-9

  • Online ISBN: 978-3-319-27863-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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