面向子事件识别的本体语境增强

S. Rafatirad, R. Jain
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引用次数: 5

摘要

随着技术的进步和廉价存储的扩散,数字多媒体交互的高速率表明计算机用户越来越需要一个体面的应用程序来以有意义的方式组织个人媒体。在本文中,我们希望根据个人媒体所报道的子事件来组织个人媒体。媒体与人们对与媒体相关的事件和记忆的感知之间存在语义差距。需要一个框架来解决这一差距。本文描述了一种新的基于模型的方法,用于根据捕获和表示人类经验的高级子事件划分和组织个人照片存档。由于照片是最普遍和最多产的用户生成内容形式,因此本文主要研究个人照片收藏的自动注释。我们引入了本体识别(ROntology, recognition - ontology),它是一种具有具体上下文信息的上下文感知模型,用于子事件识别。目前,我们的方法利用了R-Ontology中建模事件的气象学、空间和时间特性。个人媒体将填充R-Ontology。我们用我们的个人照片档案来测试这种方法,这些照片描述了两个不同的场景:旅行和印度婚礼。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contextual Augmentation of Ontology for Recognizing Sub-events
With the advances in technology and proliferation of cheap storage, high rate of digital multimedia interaction signifies the increasing need of computer users for a decent application to organize personal media in a meaningful way. In this paper, we want to organize personal media in terms of the sub-events they cover. A semantic gap exists between media, and people's perception of the events and memories associated with this media. A framework is needed to address such gap. This paper describes a novel model-based approach for partitioning and organizing personal photo archive in terms of high-level subevents that capture and represent human experience. Since photos are the most ubiquitous and prolific form of user generated content, we focus on the automatic annotation of personal photo collection in this paper. We introduce ROntology (Recognition-Ontology) that is a context-aware model with concrete contextual information for subevent recognition. Currently our approach utilizes the mereological, spatial and temporal properties of modeled-events in R-Ontology. Personal media will then populate R-Ontology. We tested this approach using our personal photo archive describing two different scenarios: Trip and Indianwedding.
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