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Video Retrieval Systems Methods, Techniques, Trends and Challenges

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Video Retrieval Systems Methods, Techniques, Trends and Challenges

Rahul S Patel | Gajanan P Khapre | R. M. Mulajkr


Rahul S Patel | Gajanan P Khapre | R. M. Mulajkr "Video Retrieval Systems Methods, Techniques, Trends and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1, December 2017, pp.72-81, URL: https://www.ijtsrd.com/papers/ijtsrd5862.pdf

Video Retrieval (VR) has been increasingly accustomed describe the method of retrieving desired videos from an oversized assortment on the premise of options that are extracted from the videos. The extracted options are accustomed index, classify and retrieve desired and relevant videos whereas filtering out unwanted ones. Videos are often pictured by their audio, texts, faces and objects in their frames. An individual video possesses distinctive motion options, color histograms, motion histograms, text options, audio options, features extracted from faces and objects existing in its frames. Videos containing helpful info and occupying significant house within the databases are under-utilized unless VR systems capable of retrieving desired videos by sharply choosing relevant whereas filtering out unwanted videos exist. Results have shown performance improvement (higher precision and recall values) once options appropriate to particular kinds of videos are used with wisdom. Various combinations of those options also can be accustomed reach desired performance. During this paper a fancy and wide space of VR and VR systems has been bestowed in a very comprehensive and easy approach. Processes at completely different stages in VR systems are represented in a very systematic approach. Types of options, their mixtures and their utilization ways, techniques and algorithms are shown. Numerous querying methods, a number of the options get similarity like Kullback-Leibler distance method and relevancy Feedback technique are mentione dlike

VR, GLCM, Gabor Magnitude, Kullback-Leibler Distance Method, Relevance Feedback Method.

Volume-2 | Issue-1, December 2017
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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