TITLE:
Hand Gesture Recognition Using Appearance Features Based on 3D Point Cloud
AUTHORS:
Yanwen Chong, Jianfeng Huang, Shaoming Pan
KEYWORDS:
Human-Computer-Interaction, Gesture Recognition, 3D Point Cloud, Depth Image
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.9 No.4,
April
18,
2016
ABSTRACT: This paper presents a method for hand
gesture recognition based on 3D point cloud. Digital image processing
technology is used in this research. Based on the 3D point from depth camera,
the system firstly extracts some raw data of the hand. After the data
segmentation and preprocessing, three kinds of appearance features are
extracted, including the number of stretched fingers, the angles between
fingers and the gesture region’s area distribution feature. Based on these
features, the system implements the identification of the gestures by using
decision tree method. The results of experiment demonstrate that the proposed
method is pretty efficient to recognize common gestures with a high accuracy.