Cricket video highlight generation methods : a review
Shingrakhia, Hansa (Gujarat Technological University)
Patel, Hetal (Patel Institute of Technology and Engineering)

Date:	2022
Abstract:	The key events extraction from a video for the best representation of its contents is known as video summarization. In this study, the game of cricket is specifically considered for extracting important events such as boundaries, sixes and wickets. The cricket video highlight generation frameworks require extensive key event identification. These key events can be identified by extracting the audio, visual and textual features from any cricket video. The prediction accuracy of the cricket video summarization mainly depends on the game rules, player's form, their skill, and different natural conditions. This paper provides a complete survey of latest research in cricket video summarization methods. It includes the quantitative evaluation of the outcomes of the existing frameworks. This extensive review highly recommended developing deep learning-assisted video summarization approaches for cricket video due to their more representative feature extraction and classification capability than the conventional edge, texture features, and classifiers. The scope of this analysis also includes future visions and research opportunities in cricket highlight generation.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Cricket video summarization ; Shot boundary detection ; Key frame extraction ; Excitement and event-driven highlight generation
Published in:	ELCVIA. Electronic letters on computer vision and image analysis, Vol. 21 Núm. 2 (2022) , p. 1-22 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1465
DOI: 10.5565/rev/elcvia.1465

36 p, 773.1 KB

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