A Comprehensive Survey on Detection of Video Transitions

Year : 2025 | Volume : 12 | Issue : 03 | Page : 17 26
    By

    Ayushi P. Yeram,

  • Shrikant P. Chavate,

  1. Research Scholar, Department of Electronics and Communication Engineering, G H Raisoni University, Amravati, Nimbhora, Maharashtra, India
  2. Associate Professor, Department of Electronics and Communication Engineering, G H Raisoni University, Amravati, Nimbhora, Maharashtra, India

Abstract

Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an in-depth review of the techniques and methodologies applied in shot boundary detection, with particular attention to the detection of gradual transitions such as wipes and dissolves. These types of transitions are often more challenging to detect compared to abrupt cuts due to their subtle and progressive nature. The study examines various preprocessing methods, feature extraction techniques, and similarity measurement approaches used to accurately detect these gradual transitions. Furthermore, the study analyzes and compares the performance of different SBD methods based on standard evaluation metrics such as precision, recall, and F1-score. A comparative review of several benchmark datasets is also presented to highlight the effectiveness of each method. This comprehensive analysis aims to guide researchers and developers in choosing the most appropriate techniques for specific video analysis applications.

Keywords: Walsh-Hadamard transform, speeded-up-robust feature, dynamic mode decomposition, convolutional neural network, Squared Tchebichef-Krawtchouk polynomial, Kirsh directional derivative, singular value decomposition, sparse coding

[This article belongs to Journal of Multimedia Technology & Recent Advancements ]

How to cite this article:
Ayushi P. Yeram, Shrikant P. Chavate. A Comprehensive Survey on Detection of Video Transitions. Journal of Multimedia Technology & Recent Advancements. 2025; 12(03):17-26.
How to cite this URL:
Ayushi P. Yeram, Shrikant P. Chavate. A Comprehensive Survey on Detection of Video Transitions. Journal of Multimedia Technology & Recent Advancements. 2025; 12(03):17-26. Available from: https://journals.stmjournals.com/jomtra/article=2025/view=227120


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 20/06/2025
Accepted 01/07/2025
Published 15/09/2025
Publication Time 87 Days
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