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A 3D gesture recognition framework based on hierarchical visual attention and perceptual organization models

机译:基于分层视觉注意力和感知组织模型的3D手势识别框架

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摘要

Human vision can perceive body movements and actions effortlessly. In contrast, it is still a very challenging task for machines to have comparable performance. Many research results have shown that both visual attention and perceptual organization are crucial for visual perception tasks. In recent years, gesture recognition for HCI has drawn more attention because of high application demands. Based on visual perceptual theories and hypotheses, we propose a 3D gesture recognition framework in a coherent and biologically plausible manner. It mainly includes perceptual gesture feature extraction, hierarchical salience map construction and qualitative reasoning for gesture recognition.
机译:人类的视觉可以毫不费力地感知身体的动作。相反,要使机器具有可比的性能,仍然是一项非常艰巨的任务。许多研究结果表明,视觉注意力和感知组织对于视觉感知任务都至关重要。近年来,由于高应用需求,用于HCI的手势识别引起了更多关注。基于视觉感知理论和假设,我们以连贯且生物学上合理的方式提出了3D手势识别框架。它主要包括感知手势特征提取,层次显着图构造和手势识别的定性推理。

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