Video content analysis and retrieval system using video storytelling and indexing techniques

Abstract

Videos are used often for communicating ideas, concepts, experience, and situations, because of the significant advances made in video communication technology. The social media platforms enhanced the video usage expeditiously. At, present, recognition of a video is done, using the metadata like video title, video descriptions, and video thumbnails. There are situations like video searcher requires only a video clip on a specific topic from a long video. This paper proposes a novel methodology for the analysis of video content and using video storytelling and indexing techniques for the retrieval of the intended video clip from a long duration video. Video storytelling technique is used for video content analysis and to produce a description of the video. The video description thus created is used for preparation of an index using wormhole algorithm, guarantying the search of a keyword of definite length L, within the minimum worst-case time. This video index can be used by video searching algorithm to retrieve the relevant part of the video by virtue of the frequency of the word in the keyword search of the video index. Instead of downloading and transferring a whole video, the user can download or transfer the specifically necessary video clip. The network constraints associated with the transfer of videos are considerably addressed.

Understanding users’ negative emotions and continuous usage intention in short video platforms

“…Many scholars have studied how these videos increase user activity and immersion, how to produce content, commercial marketing, system management, how to optimize recommendation algorithms, video technology, the flow experience of using short video platforms, etc. (Davis, 2019;Huang et al, 2022;Jacob et al, 2020). Other scholars have studied the negative effects of short video platforms on users.…”

Enhancing multi-class web video categorization model using machine and deep learning approaches

“…YouTube is known as the largest repository of videos and is widely used for video sharing by billions of users [1]- [4]. However, given the massive number of videos on the web, users face difficulties in accurately retrieving and obtaining the videos they need [5], [6]. The best method to examine, extract and classify web videos on the basis of content similarity is web video categorization (WVC) [7]- [10].…”