Human Action Recognition Using a Semantic-Probabilistic Network

被引:0
|
作者
Kovalenko, Mykyta [1 ]
Antoshchuk, Svetlana [1 ]
Sieck, Juergen [2 ]
机构
[1] Odessa Natl Polytech Univ, Odessa, Ukraine
[2] Univ Appl Sci Berlin HTW, Berlin, Germany
来源
2015 INTERNATIONAL CONFERENCE ON EMERGING TRENDS IN NETWORKS AND COMPUTER COMMUNICATIONS (ETNCC) | 2015年
关键词
ontology; Bayesian network; event recognition; gesture recognition; human actions; surveillance systems; semantic-probabilistic network;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper we propose a semantic-probabilistic network to recognise human actions. We use a predefined domain ontology to describe the events and scenarios in the scene as a hierarchical decomposition of simple concepts and variables and then perform an automated conversion of the ontology into a Bayesian network. A novel approach for Bayesian network nodes' weights calculation is introduced based on the weighted relation between concepts of the ontology in order to reduce the influence of incorrect object detection. We then evaluate the performance of our approach using it to predict gestures in a human gesture recognition system, using a set of pre-recorded video sequences.
引用
收藏
页码:67 / 72
页数:6
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