Hand Gesture Recognition Using Microsoft ’ s Kinect
Hand Gesture Recognition Using Microsoft ’ s Kinect
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使用 Microsoft Kinect 进行手势识别
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Dr. Amitabha Mukerjee
中科院分区：
文献类型：
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作者：
Shashank Sonkar;Akshay Kumar;Dr. Amitabha Mukerjee
手势是向计算机发出命令或与机器人通信的最自然的方式之一。另一种可能的可能性是语音识别，需要计算机/机器人进行大量学习，因为它是特定于用户的。在这个项目中，我们使用Kinect获得的z深度来准确地确定不同的手势。低成本微软 Kinect 的出现提供了新的机遇，并刺激了人机交互 (HCI) 领域的研究。然而，手势识别仍然是 Kinect 相对未开发的方面。由于手部相对人体而言较小且形状复杂，因此手部识别的复杂性进一步使情况变得复杂。我们使用一种新颖的距离度量方法来计算两个不同手势手指-地球距离（FEMD）之间的差异。
Hand Gesture is one of the most natural ways to give commands to the computer or communiate with a robot. The other plausible possibility, speech recognition, requires a lot of learning to be done on part of the computer/robot as it is user specific. In this project, we use z-depth obtained by Kinect to determine accurately different hand gestures. The advent of low cost Microsoft’s Kinect has provided new opportunities & spurred research in areas of human-computer interaction (HCI).However, Hand Gesture Recognition remains a relatively unexplored facet of Kinect. The complexities involved in hand recognition owing to its small size relative to the human body & its complex shape further complicates the scenario. We use a novel distance metric method for computing dissimilarity between two different hand gestures Finger-Earth over’s Distance (FEMD).