Java automatic semantic content extraction in videos using a fuzzy ontology and rule-based model
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This document proposes a semantic content extraction system for videos using a fuzzy ontology and rule-based model. The system allows users to automatically query and retrieve objects, events, and concepts extracted from videos. It introduces an ontology-based fuzzy video semantic content model that uses spatial and temporal relations in event and concept definitions. This model provides a standard for constructing domain ontologies and additional rules to define complex situations and lower computational costs. The framework has been implemented and tested across three domains, achieving satisfactory precision and recall for object, event, and concept extraction.
Java automatic semantic content extraction in videos using a fuzzy ontology and rule-based model
- 1. AUTOMATIC SEMANTIC CONTENT EXTRACTION IN VIDEOS USING A FUZZY ONTOLOGY AND RULE-BASED MODEL 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. 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. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: [email protected]