Volume No. :   11

Issue No. :  2

Year :  2019

ISSN Print :  0975-4393

ISSN Online :  2349-2988


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Comparative analysis on video retrieval technique using machine learning



Address:   S. Sasireka
Department of CSE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India 638401
*Corresponding Author
DOI No: 10.5958/2349-2988.2019.00022.6

ABSTRACT:
The objective of information mining is to find and portray fascinating examples in information. This errand is particularly testing when the information comprise of video arrangements (which may likewise have sound substance), due to the need to break down colossal volumes of multidimensional information. The lavishness of the space suggests that a wide range of methodologies can be taken and a wide range of instruments and systems can be utilized, as can be found in the sections of this book. They manage grouping and arrangement, signals and characters, division and rundown, insights and semantics. No endeavor will be made here to drive these subjects into a straightforward structure. In the creators' own (sometimes shortened) words, the sections manage video perusing utilizing various synchronized perspectives; the physical setting as a video mining crude; transient video limits; video rundown utilizing action and sound descriptors; content examination utilizing multimodal data; video OCR; video arrangement utilizing semantics and semiotics; the semantics of media; measurable procedures for video investigation and seeking; mining of factual worldly structures in video; and pseudo-pertinence criticism for sight and sound recovery.
KEYWORDS:
Bag of features (Bof), histograms, Support Vector Machines, keypoint locations
Cite:
S. Sasireka. Comparative analysis on video retrieval technique using machine learning. Research J. Science and Tech. 2019; 11(2):148-154.
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