Visual Information Retrieval for Videos Based on Feature Extraction using Machine Learning Techniques
V.Mohana Maniganda Babu1, S.Sasireka2, E.Anitha3
1V.Mohana Maniganda Babu, School of IT & Science, DR.G.R. Damodaran College of Science, Coimbatore.
2S.Sasireka, Department of Computer Science and Engineering, Bannari Amman Institute ofTechnology, Sathyamnagalam, Erode.
3E.Anitha, Department of Computer Science and Engineering,Bannari Amman Institute of Technology, Sathyamnagalam, Erode.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 29 June 2020 | PP: 29-34 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J100508810S19/2019©BEIESP | DOI: 10.35940/ijitee.J1005.08810S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Information retrieval is one of the important areas of research with highest scope for data mining combined with machine learning. The proposed research focus on visual information retrieval by applying machine learning techniques. The usage of multimedia data such as text, images, videos are abundantly increasing day by day in this smart era. Also the need for information classification and retrieval are getting exponential demands to fulfill the research and end user requirements. The tech giants are conducting their researches to develop efficient retrieval systems for videos. Video retrieval is considered to be the toughest and challenging research in the recent times. Due to large storage space, lengthy play time, multiple sequence of frames, spatial temporal challenges, lack of visual relevancy, less hardware and processing support. The proposed visual information retrieval has got higher scope of research with the above listed problems.
Keywords: Bag of Features (Bof), Histograms, Support Vector Machines, key Point Locations-Means Algorithm.
Scope of the Article: Information Retrieval