SWAV: Semantics-Based Workflows for Automatic Video Analysis

被引：0
|
作者：
Nadarajan, Gayathri [1 ]
Chen-Burger, Yun-Heh [1 ]
Fisher, Robert B. [1 ]
机构：
[1] Univ Edinburgh, Sch Informat, Edinburgh EH8 9YL, Midlothian, Scotland
来源：
AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGIES AND APPLICATIONS | 2011年 / 6682卷
关键词：
semantics based workflows; ontologies; HTN planning; requirements based virtual workflow system; intelligent video processing;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper outlines the SWAV system - Semantics-based Workflows for Automatic Video Analysis. SWAV utilises ontologies and planning as core technologies to gear the composition and execution of video processing workflows. It is tailored for users without image processing expertise who have specific goals (tasks) and restrictions on these goals but not the ability to choose appropriate video processing software to solve their goals. An evaluation on a set of ecological videos has indicated that SWAV: 1) is more time-efficient at solving video classification tasks than manual processing; 2) is more adaptable in response to changes in user requests (task restrictions and video descriptions) than modifying existing image processing programs; and 3) assists the user in selecting optimal solutions by providing recommended descriptions.
引用
收藏
页码：681 / 691
页数：11
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