Crucial Video Content Extraction Using Ontology Rule-based Technology and Decision Making Algorithm

被引:0
作者
Nandhini, R. P. Ramya [1 ]
Valarmathie, P. [1 ]
机构
[1] Saveetha Engn Coll, Madras, Tamil Nadu, India
来源
2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND SYSTEMS (ICCCS'14) | 2014年
关键词
Semantic content extraction; Ontology; Metaontology; Fuzzy; Decision making;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Interpreting and extracting the content from video is fascinating issue to focus in many video based applications especially in mission critical situations. Many facilities exist in video processing that generates raw data and low level features namely color, texture and format which are not enough in complex data analysis of video application. Semantic level features from the video need to be extracted to meet the requirement of high level video processing. This paper explores the extraction technique of semantic level features such as object, event and concepts automatically. Crucial video content extraction model exploits Spatio-temporal relations in addition to concept and event definitions. Meta-Ontology presents a domain-independent rule generation standard that enables the user to generate ontological model for a specific domain. Using decision making algorithm, one can derive a decision of the occurrence of particular event. Rule definitions assist in lowering the computation cost of spatial relation and define the complex situation effectively. Efficacy of the proposed technique is evaluated in terms of precision and recall rates of the extraction of semantic level features.
引用
收藏
页码:81 / 85
页数:5
相关论文
共 11 条
[1]  
[Anonymous], THESIS
[2]  
GOMEZPEREZ A, 2004, ADV INFORM KNOWLEDGE
[3]  
Hakeem A, 2005, P 20 NAT C ART INT A, P89
[4]   Video-based event recognition: activity representation and probabilistic recognition methods [J].
Hongeng, S ;
Nevatia, R ;
Bremond, F .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2004, 96 (02) :129-162
[5]   Event detection and analysis from video streams [J].
Medioni, G ;
Cohen, I ;
Brémond, F ;
Hongeng, S ;
Nevatia, R .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2001, 23 (08) :873-889
[6]  
Nepal S., 2001, ACM Multimedia, P261
[7]   Content-based video retrieval by integrating spatio-temporal and stochastic recognition of events [J].
Petkovic, M ;
Jonker, W .
IEEE WORKSHOP ON DETECTION AND RECOGNITION OF EVENTS IN VIDEO, PROCEEDINGS, 2001, :75-82
[8]  
Petkovic M, 2000, P INT C ADV INFR E B
[9]   Rapid estimation of camera motion from compressed video with application to video annotation [J].
Tan, YP ;
Saur, DD ;
Kulkarni, SR ;
Ramadge, PJ .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2000, 10 (01) :133-146
[10]  
Xu M, 2004, LECT NOTES COMPUT SC, V3333, P566