Sports highlights generation using decomposed audio information

Research output: Book chapter/Published conference paperConference paper

Abstract

Visual features are generally used in video summarization including sports videos. However, audio features are also important in summarization as they characterize the exciting events of a sport, especially when external thing e.g. raining effects the visual feature. The commentator’s voice, referee’s whistle, and audience-voice are strongly correlated to the exciting events e.g. goal, penalty shootout, red card, etc. in a soccer game. The existing methods using original audio signals could not provide expected summary due to the various noises from the audience such as horn and sound from various musical instruments. In this paper, we propose a novel approach to extract audio features using Empirical Mode Decomposition (EMD) that can filter out noises. We have conducted a set of experiments on four real soccer videos. The experimental results demonstrate that the proposed method can detect goal events with 96% accuracy which outperforms the existing state-of-the-art method by 42%.
Original languageEnglish
Title of host publicationIEEE International Conference on Multimedia and Expo
Place of PublicationUnited States
PublisherIEEE Xplore
Pages579-584
Number of pages6
DOIs
Publication statusPublished - 2019
EventIEEE International Conference on Multimedia and Expo (ICME) 2019 - Shanghai International Convention Center, Shanghai, China
Duration: 08 Jul 201912 Jul 2019
https://www.icme2019.org/

Conference

ConferenceIEEE International Conference on Multimedia and Expo (ICME) 2019
CountryChina
CityShanghai
Period08/07/1912/07/19
Internet address

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