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Event recognition using object-motion context

机译:使用对象运动上下文进行事件识别

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摘要

Context based recognition system, which can improve the accuracy of scene recognition if robots cannot obtain adequate recognition features in the camera, has attracted researchers recently. However, there are few researches which focus on part-whole supplement system based on context which can describe the scene using detail parts in the scene and also reduce the ambiguity of each detail part using sentences in reverse. In this paper, we constructed the mutual supplement model focused on the ontological relationship between object and motion. We will take desk work in this research as an example of the experiment and show the usefulness of proposed model which can increase the recognition probability values of object and motion.
机译:基于上下文的识别系统最近吸引了研究人员,该系统可以在机器人无法在相机中获得足够的识别功能时提高场景识别的准确性。然而,很少有研究集中在基于上下文的局部整体补充系统上,该系统可以使用场景中的细节部分来描述场景,并且还可以使用相反的句子来减少每个细节部分的歧义。在本文中,我们构建了以对象与运动之间的本体关系为重点的互补充模型。我们将以这项研究中的案头工作作为实验示例,并展示所提出模型的有效性,该模型可以增加物体和运动的识别概率值。

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