Dynamic and personalized video summarization towards sports entertainment

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing Pub Date : 2025-07-16 DOI:10.1016/j.entcom.2025.100999

Pulkit Narwal, Neelam Duhan, Komal Kumar Bhatia

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引用次数: 0

Abstract

Personalized video summarization involves creation of a compact yet representative version (video summary) of an input video based on individual user preferences. There exists some research gaps in existing works concerning multi-modal system, domain knowledge, effective mapping of video content and user preference. This paper covers the existing research gaps for personalized video summarization and better user entertainment experience. This paper presents a Multi-Modal Multi-module approach for dynamic and personalized video summarization of Cricket sport videos. The Multi-module architecture exploits multiple modalities of the video to select representative content according to user preferences. The proposed approach includes dynamic video segmentation strategy based on Cricket domain knowledge, and key segment selection strategy based on Umpire Detection-Umpire Pose Recognition and Score Board Optical Character Recognition. The proposed approach is quantitatively and qualitatively evaluated to observe the performance of the models and to analyse the quality of generated dynamic and personalized video summary. The performance evaluation (both quantitative and qualitative) reveals the exceptional results and promises to present this work as a standard towards video segmentation, dynamic and personalized video summarization and sports entertainment.

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面向体育娱乐的动态个性化视频总结

个性化视频摘要包括基于个人用户偏好创建一个简洁但具有代表性的输入视频版本（视频摘要）。现有研究在多模态系统、领域知识、视频内容有效映射和用户偏好等方面存在一定的研究空白。本文涵盖了个性化视频摘要和更好的用户娱乐体验的现有研究空白。提出了一种多模态多模块的板球运动视频动态个性化视频摘要方法。多模块架构利用视频的多种模式，根据用户偏好选择具有代表性的内容。该方法包括基于板球领域知识的动态视频分割策略，以及基于裁判检测-裁判姿势识别和记分牌光学字符识别的关键片段选择策略。对所提出的方法进行了定量和定性评估，以观察模型的性能，并分析生成的动态和个性化视频摘要的质量。性能评估（定量和定性）揭示了卓越的结果，并承诺将这项工作作为视频分割，动态和个性化视频摘要以及体育娱乐的标准。

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来源期刊

Entertainment Computing Computer Science-Human-Computer Interaction

CiteScore

5.90

自引率

7.10%

发文量

期刊介绍： Entertainment Computing publishes original, peer-reviewed research articles and serves as a forum for stimulating and disseminating innovative research ideas, emerging technologies, empirical investigations, state-of-the-art methods and tools in all aspects of digital entertainment, new media, entertainment computing, gaming, robotics, toys and applications among researchers, engineers, social scientists, artists and practitioners. Theoretical, technical, empirical, survey articles and case studies are all appropriate to the journal.