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Automatic Soccer Highlights Generation

Student: Slavutin Aleksandr

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 8

Year of Graduation: 2021

The video summarization problem has been actively discussed in the scientific community due to the increasing amount of video data. Current methods for solving this problem are based on the combination of convolutional neural networks, for input frame features extraction, with attention mechanism. In this paper, we test the hypothesis that models for solving the video summarization problem can be used for summarization of football matches. A comparison is made between the state-of-the-art approach for video summarization and the method based on frame-by-frame classification proposed in this paper. The comparison is carried out on a dataset created specifically for this paper.

Full text (added May 20, 2021)

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