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Visual Form 2001

Martin-Granel Pierre, Roach Matthew, Mason John, Matt Roach Orcid Logo

Lecture notes in computer science

Swansea University Author: Matt Roach Orcid Logo

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DOI (Published version): 10.1007/3-540-45129-3

Abstract

This paper considers camera motion extraction with application to automatic video classification. Video motion is subdivided into 3 components, one of which, camera motion, is considered here. The extraction of the camera motion is based on correlation. Both subjective and objective measures of the...

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Published in: Lecture notes in computer science
ISBN: 978-3-540-42120-7 978-3-540-45129-7
Published: 2001
URI: https://cronfa.swan.ac.uk/Record/cronfa39133
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Abstract: This paper considers camera motion extraction with application to automatic video classification. Video motion is subdivided into 3 components, one of which, camera motion, is considered here. The extraction of the camera motion is based on correlation. Both subjective and objective measures of the performance of the camera motion extraction are presented. This approach is shown to be simple but efficient and effective. This form is separated and extracted as a discriminant for video classification. In a simple classification experiment it is shown that sport and non-sport videos can be classified with an identification rate of 80%. The system is shown to be able to verify the genre of a short sequence (only 12 seconds), for sport and non-sport, with a false acceptance rate of 10% on arbitrarily chosen test sequences.
College: Faculty of Science and Engineering