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Index Point Detection and Semantic Indexing of Videos—A Comparative Review

  • Mehul MahrishiEmail author
  • Sudha Morwal
Conference paper
  • 22 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1154)

Abstract

Primarily used for fun and entertainment, videos are now a motivation behind social, commercial, and business activities. It is presumed that by 2025, about 75% of all Internet traffic will be of videos. In education, videos are a source of learning. Study Webs of Active Learning for Young Aspiring Minds (SWAYAM), National Programme on Technology Enhanced Learning (NPTEL), Massive Open Online Courses (MOOCs), Coursera, and many other similar platforms provide not only courseware but also beyond the curriculum contents apart from the conventional syllabi. Even at the junior level, Byju’s and similar educational portals are witnessing an explosive growth in video contents. Despite that we are now able to extract semantic features from images, video sequences and besides being ubiquitous in nature, video lectures have a limitation of smooth navigation between topics. Through this paper, we want to throw light on existing automated video indexing approaches and their prerequisites that are recently proposed. We tried to analyze them based on some existing measures.

Keywords

E-learning Lecture videos Video segmentation Video indexing Text similarity Video analysis 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Swami Keshvanand Institute of TechnologyJaipurIndia

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