Depth data acquired by current low-cost real-time depth cameras provide a very informative description of the hand pose, that can be effectively exploited for gesture recognition purposes. This paper introduces a novel hand gesture recognition scheme based on depth data. The hand is firstly extracted from the acquired depth maps with the aid also of color information from the associated views. Then the hand is segmented into palm and finger regions. Next, two different set of feature descriptors are extracted, one based on the distances of the fingertips from the hand center and the other on the curvature of the hand contour. Finally, a multiclass SVM classifier is employed to recognize the performed gestures. The proposed scheme runs in real-time and is able to achieve a very high accuracy on depth data acquired with the Kinect.

Hand gesture recognition with depth data

DOMINIO, FABIO;DONADEO, MAURO;MARIN, GIULIO;ZANUTTIGH, PIETRO;CORTELAZZO, GUIDO MARIA
2013

Abstract

Depth data acquired by current low-cost real-time depth cameras provide a very informative description of the hand pose, that can be effectively exploited for gesture recognition purposes. This paper introduces a novel hand gesture recognition scheme based on depth data. The hand is firstly extracted from the acquired depth maps with the aid also of color information from the associated views. Then the hand is segmented into palm and finger regions. Next, two different set of feature descriptors are extracted, one based on the distances of the fingertips from the hand center and the other on the curvature of the hand contour. Finally, a multiclass SVM classifier is employed to recognize the performed gestures. The proposed scheme runs in real-time and is able to achieve a very high accuracy on depth data acquired with the Kinect.
2013
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream - ARTEMIS '13
9781450323932
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2686684
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