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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19458
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 145
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| Paper Title: | Automation of Video Annotation Using Textual Description: A Comprehensive Survey |
| Authors Name: | Neha B A , Dr. Bhagyashree Ambore , Ganesh Channakrishnam Sharma , Sujay Karanth , Shreyash Saxena |
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IJRTI_188899
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| Published Paper Id: | IJRTI2401083 |
| Published In: | Volume 9 Issue 1, January-2024 |
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| Abstract: | This survey explores automatic video annotation, emphasizing its role in video understanding. Video annotation, associating metadata with video segments, aids in efficient retrieval and analysis. The paper discusses approaches, techniques, and applications, such as content-based video retrieval and activity recognition. Methods: The project aims to automate video annotations through interpreting textual descriptions. Objectives include collecting video data, employing Natural Language Processing (NLP) for information extraction, integrating computer vision for visual analysis, and ensuring a userfriendly, scalable system. Results: The expected outcome is a user-friendly system that significantly reduces human effort in video annotation. Leveraging NLP and computer vision, the system aims for precise annotations, enhancing productivity across applications, from content management to surveillance. Conclusion: The project addresses the need for automating video annotation, offering a promising solution to challenges associated with manual processes. The integration of NLP and computer vision promises to redefine video content management, providing industries with a more efficient means of annotating video content. |
| Keywords: | Automatic Video Annotation, Metadata, Content-Based Video Retrieval, Activity Recognition, Textual Descriptions, Natural Language Processing (NLP), Computer Vision, Information Extraction, Multimedia Analysis, Machine Learning |
| Cite Article: | "Automation of Video Annotation Using Textual Description: A Comprehensive Survey", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 1, page no.513 - 526, January-2024, Available :http://www.ijrti.org/papers/IJRTI2401083.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2401083
Registration ID:188899
Published In: Volume 9 Issue 1, January-2024
DOI (Digital Object Identifier):
Page No: 513 - 526 Country: Bengaluru, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2401083 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2401083 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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