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Topolet: From Atomic Hand Posture Structures to a Comprehensive Gesture Set

机译:Topolet:从原子手姿势结构到全面的手势套装

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We propose a type of time-series model for hierarchical hand posture database which can be viewed as a Markovian temporal structure. The model employs the topology of the points' cloud, existing in each layer of the database, and exploits a novel type of atomic structure, we refer to as Topolet. Moreover, our temporal structure utilizes a modified version of another atomic gesture structure, known as Poselet. That modification considers Poselets from the vector-based generative perspective (instead of the pixel-based discriminative one). The results suggest a considerable improvement in the accuracy and time-complexity. Furthermore, in contrast to other approaches, our Topolet is capable of considering random gestures, thus introduces a comprehensive set of gestures (suitable for context-free application domain) within the shape-based approach. We prove that the Topolet could be enhanced to different resolutions of gestures' set which provide the system with the potential to be adapted to different application requirements.
机译:我们提出了一种用于分层手部姿势数据库的时间序列模型,其可以被视为马尔科维亚的时间结构。该模型采用点云的拓扑,存在于数据库的每层中,并利用新颖的原子结构,我们称为Topolet。此外,我们的时间结构利用另一种原子手势结构的修改版本,称为主题。该修改考虑来自基于向量的生成透视(而不是基于像素的鉴别鉴别的poselets)。结果表明,准确性和时间复杂性的显着提高。此外,与其他方法相比,我们的Topolet能够考虑随机手势,从而在基于形状的方法内引入了一组综合的手势(适用于无内容应用域)。我们证明,Topolet可以增强到不同的手势分辨率,它为系统提供了适应不同应用要求的潜力。

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