与日常工件的原型交互:通过kinect训练和识别3D对象

Kexi Liu, Dimosthenis Kaleas, Roger Ruuspakka
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引用次数: 7

摘要

在本文中,我们探索和原型与日常被动对象的交互。我们提出了一种3D对象训练和识别方法,利用Kinect传感器:主导方向模板(DOT)方法允许实时对象训练和多个Kinect加速训练过程,同时从多个视点学习对象,并删除对象背景。基于这种方法,开发了一个概念验证的使用场景,3D实时乐高积木指导:系统提前学习单个乐高积木和乐高积木步骤;这样,用户就可以用附着在现有乐高积木上的3D视觉提示来构建乐高模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prototyping interaction with everyday artifacts: training and recognizing 3D objects via Kinects
In this paper we explore and prototype the interaction with everyday passive objects. We present an approach for 3D object training and recognition, leveraging Kinect sensors: the Dominant Orientation Templates (DOT) method allows real-time object training and multiple Kinects speed up the training process by learning the object from multiple viewpoints simultaneously with the object background removed. A proof-of-concept usage scenario, 3D real-time Lego building instruction, has been developed based on this approach: the system learns the individual Lego pieces and Lego building steps in advance; the users thus construct the Lego model with 3D visual hints attached to present Lego pieces.
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