Evaluation framework for video OCR

  • Authors:

  • Padmanabhan Soundararajan;Matthew Boonstra;Vasant Manohar;Valentina Korzhova;Dmitry Goldgof;Rangachar Kasturi;Shubha Prasad;Harish Raju;Rachel Bowers;John Garofolo

  • Affiliations:

  • Computer Science and Engineering, University of South Florida, Tampa, FL;Computer Science and Engineering, University of South Florida, Tampa, FL;Computer Science and Engineering, University of South Florida, Tampa, FL;Computer Science and Engineering, University of South Florida, Tampa, FL;Computer Science and Engineering, University of South Florida, Tampa, FL;Computer Science and Engineering, University of South Florida, Tampa, FL;VideoMining Corporation, PA;VideoMining Corporation, PA;Information Technology Lab – Information Access Division, Speech Group, National Institute of Standards and Technology (NIST);Information Technology Lab – Information Access Division, Speech Group, National Institute of Standards and Technology (NIST)

  • Venue:
  • ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
  • Year:
  • 2006

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Abstract

In this work, we present a recently developed evaluation framework for video OCR specifically for English Text but could well be generalized for other languages as well. Earlier works include the development of an evaluation strategy for text detection and tracking in video, this work is a natural extension. We sucessfully port and use the ASR metrics used in the speech community here in the video domain. Further, we also show results on a small pilot corpus which involves 25 clips. Results obtained are promising and we believe that this is a good baseline and will encourage future participation in such evaluations.