定性的空间和时间推理图的活动识别

Chayanika Deka Nath, S. Hazarika
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引用次数: 3

摘要

为了寻求视频中活动识别的有效表示模式,我们采用了将图解推理(DR)与定性时空推理(QSTR)相结合的技术。QSTR允许对感兴趣的对象之间的时空关系进行定性抽象;而且常常被模棱两可的结论所挫败。“图表”通过外化心理环境来影响认知推理。因此,QSTR比图更有希望。我们将“图表”定义为感兴趣的对象及其在二维网格上的空间信息的明确表示。提取出一系列“关键图”。图间推理运算符结合“关键图”来获得时空信息。由此获得的定性时空信息定义了短期活动(STA)。几个sta结合起来形成长期活动(LTA)。使用sta序列作为特征向量进行LTA识别。我们在来自CAVIAR数据集的六个lta上评估了我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Qualitative spatial and temporal reasoning over diagrams for activity recognition
In quest for an efficient representation schema for activity recognition in video, we employ techniques combining diagrammatic reasoning (DR) with qualitative spatial and temporal reasoning (QSTR). QSTR allows qualitative abstraction of spatio-temporal relations among objects of interest; and is often thwart by ambiguous conclusions. 'Diagrams' influence cognitive reasoning by externalizing mental context. Hence, QSTR over diagrams holds promise. We define 'diagrams' as explicit representation of objects of interest and their spatial information on a 2D grid. A sequence of 'key diagrams' is extracted. Inter diagrammatic reasoning operators combine 'key diagrams' to obtain spatio-temporal information. The qualitative spatial and temporal information thus obtained define short-term activity (STA). Several STAs combine to form long-term activities (LTA). Sequence of STAs as a feature vector is used for LTA recognition. We evaluate our approach over six LTAs from the CAVIAR dataset.
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