Fast 3D hand estimation for mobile interactions

The ubiquitous hand gesture plays an important role in the natural human machine interaction (HMI). Recently, the consumer color and depth cameras have been used to estimate hand shapes and postures for the mid-air HMI. Under the observation that 3D hand contours possess much information of hand pos...

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Bibliographic Details
Published in2016 23rd International Conference on Pattern Recognition (ICPR) pp. 979 - 984
Main Authors Yuru Pei, Gengyu Ma
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Cameras
Estimation
Mobile communication
Mobile handsets
Reliability
Shape
Three-dimensional displays
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Summary:The ubiquitous hand gesture plays an important role in the natural human machine interaction (HMI). Recently, the consumer color and depth cameras have been used to estimate hand shapes and postures for the mid-air HMI. Under the observation that 3D hand contours possess much information of hand postures, we estimate 3D hand contours from infrared images with a limited computation complexity for the HMI on mobile devices. A variant of the dynamic programming (vDP) algorithm is proposed to handle complex self-occlusions in 3D hand estimations, where a set of heuristic rules are introduced to avoid finger missing. Furthermore, the constraints are used to reduce the searching space in contour alignments. Given 3D hand contours, a set of hand gestures, including touching, swiping, and pinching, can be applied to mid-air interactions. The proposed method is much faster than the traditional depth estimation of the whole hand, and can achieve up to 500 Hz on PC, and 100 Hz on mobile devices.
DOI:10.1109/ICPR.2016.7899763