Call For Paper Volume:4 Issue:7 Jul'2017 |

VIDEO SEMANTIC CONTENT EXTRACTION USING k-MEANS and FUZZY ONTOLOGY

Publication Date : 10/07/2015



Author(s) :

Priyanka Nikam , Mr. B. R. Nandwalkar.


Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India



Abstract :

Increased use of video based applications revealed need of efficiently extracting the video contents. The video contains various features which can be classified into normal data, relative features and logic content. For core content of video semantic level understanding is required. So to get video content automatic semantic content framework is proposed. In proposed system a semantic content extraction system which allows the user to query and regain objects, events, and concepts that are extracted automatically. VISCOM is a video semantic content model which contains classes and relations between classes. Objects and events are represented by some VISCOM classes and other classes are used in the automatic semantic content extraction framework. VISCOM classes collect the semantic content types and relations. Ontology based fuzzy video data semantic model which uses spatial and temporal relations in event and concept definition is proposed. Extracted objects from consecutive representative frames are processed to extract temporal relations. Additional rules to lower spatial relation computation cost and to define some difficult situations more successfully are used. To extract objects from video we apply k-means clustering algorithm. By, which we get the more relevant objects related to user query. Keywords


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