NDLI: AR in Hand: Egocentric Palm Pose Tracking and Gesture Recognition for Augmented Reality Applications

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AR in Hand: Egocentric Palm Pose Tracking and Gesture Recognition for Augmented Reality Applications

Content Provider	ACM Digital Library
Author	Liang, Hui Yuan, Junsong Thalmann, Daniel Thalmann, Nadia Magnenat
Abstract	Wearable devices such as Microsoft Hololens and Google glass are highly popular in recent years. As traditional input hardware is difficult to use on such platforms, vision-based hand pose tracking and gesture control techniques are more suitable alternatives. This demo shows the possibility to interact with 3D contents with bare hands on wearable devices by two Augmented Reality applications, including virtual teapot manipulation and fountain animation in hand. Technically, we use a head-mounted depth camera to capture the RGB-D images from egocentric view, and adopt the random forest to regress for the palm pose and classify the hand gesture simultaneously via a spatial-voting framework. The predicted pose and gesture are used to render the 3D virtual objects, which are overlaid onto the hand region in input RGB images with camera calibration parameters for seamless virtual and real scene synthesis.
Starting Page	743
Ending Page	744
Page Count	2
File Format	PDF
ISBN	9781450334594
DOI	10.1145/2733373.2807972
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-13
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Palm pose estimation Gesture recognition Augmented reality
Content Type	Text
Resource Type	Article

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