A framework for automatic sports video annotation with anomaly detection and transfer learning

author: Teofilo De Campos, Centre for Vision, Speech and Signal Processing, University of Surrey
published: Aug. 6, 2013,   recorded: April 2013,   views: 3784


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This paper describes a system that can automatically annotate videos and illustrates its application to tennis games. A unified apparatus is proposed, cast in a Bayesian reasoning framework. This is supported by a cognitive memory architecture that allows the system to store raw video data at the lowest cognitive level and its semantic annotation with increasing levels of abstraction up to determining the score of a game. Also embedded in the system is a set of mechanisms to detect anomalies caused by a change of domain in the input data. Once an anomaly is detected, transfer learning methods are triggered to adapt the knowledge to new domains, such as new sport modalities. We also present a generic framework for rule induction that is crucial in the context of an adaptive annotation system.

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Reviews and comments:

Comment1 amersonwale, November 23, 2020 at 7:57 p.m.:

Hello, thanks for the video! I am not too much into cricket, but I really like what teams are doing, they took some good positions the last year, unfortunately, because of the Covid19 threat, cricket industry is paralyzed for some time, but I am happy that internet is working, and I can recreate myself betting on https://in.parimatch.com/hi/ and other top bookies working with Indian ruppies.

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