This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
||||||||
|
Paper Details
Paper Title
Automatic Semantic Content Extraction in Videos Using a Fuzzy Ontology and Rule-Based Model
Authors
  Satish D Mali,  Pravin P Kalyankar
Abstract
Recent increase in the use of video-based applications has revealed the need for extracting the content in videos. Raw data and low-level features alone are not sufficient to fulfill the user’s needs; that is, a deeper understanding of the content at the semantic level is required. Currently, manual techniques, which are inefficient, subjective and costly in time and limit the querying capabilities, are being used to bridge the gap between low-level representative features and high-level semantic content. Here, we propose a semantic content extraction system that allows the user to query and retrieve objects, events, and concepts that are extracted automatically. We introduce an ontology-based fuzzy video semantic content model that uses spatial/temporal relations in event and concept definitions. This metaontology definition provides a wide-domain applicable rule construction standard that allows the user to construct ontology for a given domain. In addition to domain ontologies, we use additional rule definitions (without using ontology) to lower spatial relation computation cost and to be able to define some complex situations more effectively. The proposed framework has been fully implemented and tested on three different domains. We have obtained satisfactory precision and recall rates for object, event and concept extraction.
Keywords- Keywords - Semantic content extraction, video content modeling, fuzziness, ontology
Publication Details
Unique Identification Number - IJEDR1704173Page Number(s) - 1078-1082Pubished in - Volume 5 | Issue 4 | December 2017DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Satish D Mali,  Pravin P Kalyankar,   "Automatic Semantic Content Extraction in Videos Using a Fuzzy Ontology and Rule-Based Model", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 4, pp.1078-1082, December 2017, Available at :http://www.ijedr.org/papers/IJEDR1704173.pdf
Article Preview
|
|
||||||
|