An Innovative Video Summary and Pattern Mining using VSP Algorithm
N. Venkatesvara Rao1, D.V.V. Prasad2, D. Susitra3
1N. Venkatesvara Rao, Assistant Professor Selection Grade, Department of Computer Science and Engineering, Saveetha Institute of Medical Sciences and Technology, Chennai (Tamil Nadu), India.
2D.V.V. Prasad, Professor, Department of Computer Science and Engineering, SSN College of Engineering, (Tamil Nadu), India.
3D. Susitra, Associate Professor, Department of Electrical and Electronics Engineering, Sathyabama Institute of Science and Technology, (Tamil Nadu), India.
Manuscript received on 03 October 2019 | Revised Manuscript received on 12 October 2019 | Manuscript Published on 22 October 2019 | PP: 610-614 | Volume-8 Issue-3S October 2019 | Retrieval Number: C11221083S19/2019©BEIESP | DOI: 10.35940/ijrte.C1122.1083S19
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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: This paper proposes a VSP-TREE algorithm that mines l associations from video. A tool is designed to annotate the Video sequences by giving appropriate values to the sequence and then these values are converted into two-dimensional datasets suitable for clustering. The datasets are clustered using innovative algorithm to form distinct group and known as summary candidate with user size, our system make summary by choosing important frame from candidate cluster and put them in original. A VSP-TREE Based Mining method is used find out frequent patterns occurrence in the video. Association mining algorithm used on clustered datasets with innovative method, Video sequential pattern Tree (VSP Tree) Structure to generate frequent patterns through efficient methodology called conditional search.
Keywords: Video, Clustering, Datasets, Sequence and Mining.
Scope of the Article: Software Design Patterns