Freehand Push-Gesture Recognition via 3D Palm Trajectory Modeling

Shih-Yao Lin, Chuen-Kai Shie, Chu-Song Chen, Y. Hung
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Abstract

This paper aims at improving the recognition of 3D push-hand gesture, which can trigger a target selection command with our hands in the air. Although general 3D push-gesture recognizers have been developed and widely used for this purpose, a severe weakness of the current push-recognizers is that they are instable to askew-pushing problems that happen frequently in practice. It is because that the push trajectory of our hand is not always a straightforward movement due to the anatomy of human, but would vary depending on the location of the target relative to the users. We explore the 3D palm trajectories of push-gestures in different locations around the user, and propose a 3D push-gesture modeling approach by learning 3D palm trajectories to solve the askew-click problem. We evaluate the proposed recognizers on a click-gesture dataset, and compare it with the prior arts of forward-push recognizers. Experimental results demonstrate that our approach achieves higher recognition accuracies than existing approaches.
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徒手推-手势识别通过三维手掌轨迹建模
本文旨在改进三维手推手势的识别,该手势可以用我们的手在空中触发目标选择命令。虽然目前已经开发出了通用的三维推手势识别器,并广泛用于此目的,但目前的推手势识别器存在一个严重的弱点,即在实际应用中经常发生的推斜问题不稳定。这是因为由于人体的解剖结构,我们的手的推动轨迹并不总是一个直截了当的运动,而是会根据目标相对于用户的位置而变化。我们探索了用户周围不同位置的3D掌纹轨迹,并提出了一种通过学习3D掌纹轨迹来解决点击歪斜问题的3D掌纹建模方法。我们在点击手势数据集上评估了所提出的识别器,并将其与前推识别器的现有技术进行了比较。实验结果表明,该方法比现有方法具有更高的识别精度。
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