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Key-frame Extraction With Semantic Graphs in Assembly Processes

机译:装配过程中具有语义图的关键帧提取

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In this letter, we present a novel method for key-frame extraction in assembly processes, with the support of visual sensors. The method is based on the construction of a sequence of weighted graphs containing the semantics of the underlying scene, encoded as primitive temporal and spatial relations between the involved objects. The objects are modeled as three-dimensional ellipsoids, with the formulation of the minimum volume covering ellipsoid problem as a convex optimization program, which is solved by an efficient algorithm. The new models are used in the sequence of actions–relations to increase the accuracy of the key-frame extraction, by extending the states encoded in the graphs. We present and analyze the method, followed by preliminary experimental results, and provide significant evidence on its potential.
机译:在这封信中,我们提出了一种在视觉传感器支持下在装配过程中提取关键帧的新颖方法。该方法基于包含基础场景的语义的一系列加权图的构建,这些加权图被编码为所涉及对象之间的原始时间和空间关系。将对象建模为三维椭圆体,将覆盖椭圆体的最小体积的公式表示为凸优化程序,并通过有效的算法对其进行求解。通过扩展图形中编码的状态,这些新模型用于一系列的动作关系中,从而提高了关键帧提取的准确性。我们介绍并分析该方法,然后给出初步的实验结果,并提供有关其潜力的重要证据。

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