Generating Highlights of Cricket Video using Commentators and Spectators Voice
Mohammed Inayathulla1, C Karthikeyan2
1Mohammed Inayathulla1, Research Scholar, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
2C Karthikeyan2, Associate Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 10134-10136 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4261118419/2019©BEIESP | DOI: 10.35940/ijrte.D4261.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Videos are one of the important and richest sources of data on internet. In this growing world of digital technology video summarization will be handy in analysing the video data. Recently Natural Language Processing has attracted more researchers to work to meet the current emerging challenges. Among the various issues, video summarization got more focus and in this regard, many applications and works have been evolved. Video Summarization is the process of creating a small video describing the actual video within short duration(s). The paper focuses on generating highlights of a cricket video by analysing the voice of commentator and spectators. The experimental results have shown good performance when compared with human generated summary.
Keywords: Classification, Deep Learning, Excitement, Video Summarization.
Scope of the Article: Classification.