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2016 23rd International Conference on Pattern Recognition (ICPR), 2016, p.979-984
Ort / Verlag
IEEE
Erscheinungsjahr
2016
Link zum Volltext
Quelle
IEEE Electronic Library (IEL)
Beschreibungen/Notizen
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.