OcrV1, Main, Curation, bibRecord, 001075

Evaluation Framework for Video OCR

Identifieur interne : 001075 ( Main/Curation ); précédent : 001074; suivant : 001076

Evaluation Framework for Video OCR

Auteurs : Padmanabhan Soundararajan [États-Unis] ; Matthew Boonstra [États-Unis] ; Vasant Manohar [États-Unis] ; Valentina Korzhova [États-Unis] ; Dmitry Goldgof [États-Unis] ; Rangachar Kasturi [États-Unis] ; Shubha Prasad [États-Unis] ; Harish Raju [États-Unis] ; Rachel Bowers ; John Garofolo

Source :

Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.

RBID : ISTEX:8AFF4B0AF7E9D0FE474627C92962987963C951F5

Descripteurs français

Pascal (Inist)
- Métrique, Pistage, Poursuite cible, Recherche information, Reconnaissance caractère, Reconnaissance optique caractère, Signal vidéo, Texte, Traitement image, Vision ordinateur.

English descriptors

KwdEn :
- Character recognition, Computer vision, Image processing, Information retrieval, Metric, Optical character recognition, Target tracking, Text, Tracking, Video signal.

Abstract

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.

Url:

https://api.istex.fr/document/8AFF4B0AF7E9D0FE474627C92962987963C951F5/fulltext/pdf

DOI: 10.1007/11949619_74

Links toward previous steps (curation, corpus...)

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Shubha Prasad

<affiliation><wicri:noCountry code="no comma">E-mail: sprasad@videomining.com</wicri:noCountry>
</affiliation>

Harish Raju

<affiliation><wicri:noCountry code="no comma">E-mail: hraju@videomining.com</wicri:noCountry>
</affiliation>

Rachel Bowers

<affiliation><wicri:noCountry code="subField">(NIST)</wicri:noCountry>
</affiliation>

<affiliation><wicri:noCountry code="no comma">E-mail: rachel.bowers@nist.gov</wicri:noCountry>
</affiliation>

Rachel Bowers

<affiliation><wicri:noCountry code="no comma">E-mail: rachel.bowers@nist.gov</wicri:noCountry>
</affiliation>

John Garofolo

<affiliation><wicri:noCountry code="subField">(NIST)</wicri:noCountry>
</affiliation>

<affiliation><wicri:noCountry code="no comma">E-mail: john.garofolo@nist.gov</wicri:noCountry>
</affiliation>

John Garofolo

<affiliation><wicri:noCountry code="no comma">E-mail: john.garofolo@nist.gov</wicri:noCountry>
</affiliation>

Le document en format XML

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<front><div type="abstract" xml:lang="en">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.</div>
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<front><div type="abstract" xml:lang="en">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.</div>
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Evaluation Framework for Video OCR

Evaluation Framework for Video OCR

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