A New Framework for Video Data Retrieval using Hierarchical Clustering Technique
D. Saravanan1, J. Surendiran2
1D.Saravanan, Department of Operations & IT, ICFAI Business School IBS, Hyderabad (Telangana), India.
2J.Surendiran, Professor, HKBKCE, Bangalore (Karnataka), India.
Manuscript received on 01 November 2019 | Revised Manuscript received on 13 November 2019 | Manuscript Published on 22 November 2019 | PP: 2052-2055 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F13890986S319/19©BEIESP | DOI: 10.35940/ijeat.F1389.0986S319
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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: The amount of information produced every year is rapidly growing due to many factor among all media, video is a particular media embedding visual, motion, audio and textual information. Given this huge amount of information we need general framework for video data mining to be applied to the raw videos (surveillance videos, news reading, Person reading books in library etc.).We introduce new techniques which are essential to process the video files. The first step of our frame work for mining raw video data in grouping input frames to a set of basic units which are relevant to the structure of the video. The second step is charactering the unit to cluster into similar groups, to detect interesting patterns. To do this we extract some features (object, colors etc.)From the unit. A histogram based color descriptors also introduced to reliably capture and represent the color properties of multiple images. The preliminary experimental studies indicate that the proposed framework is promising.
Keywords: Data Mining, Video Segmentations, Video Data Mining, Clustering, Histogram, Video Data Clustering.
Scope of the Article: Clustering