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Motion-based classification of cartoons

Roach M., Mason J.S., Pawlewski M., Matt Roach Orcid Logo

Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489)

Swansea University Author: Matt Roach Orcid Logo

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DOI (Published version): 10.1109/ISIMP.2001.925353

Abstract

This paper describes a simple high-level classification of multimedia broadcast material into cartoon non-cartoon. The input video sequences are from a broad range of material which is representative of entertainment viewing. Classification of this type of high-level video genre is difficult because...

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Published in: Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489)
Published: 2001
URI: https://cronfa.swan.ac.uk/Record/cronfa39142
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Abstract: This paper describes a simple high-level classification of multimedia broadcast material into cartoon non-cartoon. The input video sequences are from a broad range of material which is representative of entertainment viewing. Classification of this type of high-level video genre is difficult because of its large inter-class variation. The task is made more difficult when classification is over a small time (10's of seconds) introducing a great deal of intra-class variation. This paper presents a purely dynamic based approach for content-based classification of video sequences in the form of a new global motion measure of foreground objects. Experiments are reported on a diverse database consisting of: 8 cartoon and 20 non-cartoon sequences. Results are shown in identification error rates against time of sequence used for classification. The system produces a best identification error rate of 3% on 66 separate decisions based on 23 second sequences trained using a total of ~20 minutes of video