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Semantics and Planning Based Workflow Composition for Video Processing

机译:基于语义和计划的视频处理工作流组合

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摘要

This work proposes a novel workflow composition approach that hinges upon ontologies and planning as its core technologies within an integrated framework. Video processing problems provide a fitting domain for investigating the effectiveness of this integrated method as tackling such problems have not been fully explored by the workflow, planning and ontological communities despite their combined beneficial traits to confront this known hard problem. In addition, the pervasiveness of video data has proliferated the need for more automated assistance for image processing-naive users, but no adequate support has been provided as of yet. The integrated approach was evaluated on a video set originating from open sea environment of varying quality. Experiments to evaluate the efficiency, adaptability to user's changing needs and user learnability of this approach were conducted on users who did not possess image processing expertise. The findings indicate that using this integrated workflow composition and execution method: (1) provides a speed up of over 90 % in execution time for video classification tasks using full automatic processing compared to manual methods without loss of accuracy; (2) is more flexible and adaptable in response to changes in user requests than modifying existing image processing programs when the domain descriptions are altered; and (3) assists the user in selecting optimal solutions by providing recommended descriptions.
机译:这项工作提出了一种新颖的工作流组合方法,该方法依赖于本体和规划作为其在集成框架内的核心技术。视频处理问题为研究这种集成方法的有效性提供了一个合适的领域,因为尽管工作流,规划和本体论社区结合了共同的有益特性来应对这一已知的难题,但尚未充分探讨解决这些问题的方法。另外,视频数据的普遍性激增了对天真的图像处理用户提供更多自动化协助的需求,但是到目前为止还没有提供足够的支持。在源自质量不同的公海环境的视频集上对综合方法进行了评估。在没有图像处理专业知识的用户上进行了评估效率,对用户不断变化的需求的适应性以及该方法的用户可学习性的实验。研究结果表明,使用这种集成的工作流程组成和执行方法:(1)与手动方法相比,使用全自动处理的视频分类任务的执行时间加快了90%以上,而不会损失准确性; (2)与更改域描述时修改现有的图像处理程序相比,响应用户请求的更改更灵活,更适应; (3)通过提供建议的描述来帮助用户选择最佳解决方案。

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