SPNet: A deep network for broadcast sports video highlight generation. (April 2022)
- Record Type:
- Journal Article
- Title:
- SPNet: A deep network for broadcast sports video highlight generation. (April 2022)
- Main Title:
- SPNet: A deep network for broadcast sports video highlight generation
- Authors:
- Khan, Abdullah Aman
Shao, Jie - Abstract:
- Abstract: Professionally broadcasted sports videos usually have long durations but contain only a few exciting events. In general, professional bodies and amateur content creators spend thousands of man-hours to manually crop the exciting video segments from these long-duration videos and generate handcrafted highlights. Sports enthusiasts keep them updated with the latest happening based on such highlights. There exists a need for a method that accurately and automatically recognizes the exciting activities in a sports game. To address this issue, we present a deep learning-based network SPNet that recognizes exciting sports activities by exploiting high-level visual feature sequences and automatically generates highlights. The proposed SPNet utilizes the strength of 3D convolution networks and Inception blocks for accurate activity recognition. We divide the sports video excitement into views, actions, and situations. Moreover, we provide 156 new annotations for about twenty-three thousand videos of the SP-2 dataset. Extensive experiments are conducted using two datasets SP-2 and C-sports, and the results demonstrate the superiority of the proposed SPNet. Our proposed method achieves the highest performance for views, action, and situation activities with an average accuracy of 76% on the SP-2 dataset and 82% on the C-sports dataset.
- Is Part Of:
- Computers & electrical engineering. Volume 99(2022)
- Journal:
- Computers & electrical engineering
- Issue:
- Volume 99(2022)
- Issue Display:
- Volume 99, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 99
- Issue:
- 2022
- Issue Sort Value:
- 2022-0099-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-04
- Subjects:
- Sports video -- Video analysis -- Video summarization -- Highlight extraction
Computer engineering -- Periodicals
Electrical engineering -- Periodicals
Electrical engineering -- Data processing -- Periodicals
Ordinateurs -- Conception et construction -- Périodiques
Électrotechnique -- Périodiques
Électrotechnique -- Informatique -- Périodiques
Computer engineering
Electrical engineering
Electrical engineering -- Data processing
Periodicals
Electronic journals
621.302854 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00457906/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compeleceng.2022.107779 ↗
- Languages:
- English
- ISSNs:
- 0045-7906
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.680000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21058.xml