A Static Hand Gesture Recognition Method Based on the Depth Information

2016 ◽  
Author(s):  
Li Ma ◽  
Wenjing Huang
Keyword(s):  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Depth Information ◽  
Recognition Method

Feature Fusion Based Hand Gesture Recognition Method for Automotive Interfaces

2020 ◽  
Vol 29 (6) ◽  
pp. 1153-1164
Author(s):  
Qianyi Xu ◽  
Guihe Qin ◽  
Minghui Sun ◽  
Jie Yan ◽  
Huiming Jiang ◽  
...  
Keyword(s):  
Gesture Recognition ◽  
Feature Fusion ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Recognition Method

scholarly journals A Decision Tree based Real-time Hand Gesture Recognition Method using Kinect

2013 ◽  
Vol 16 (12) ◽  
pp. 1393-1402 ◽  
Author(s):  
Guochao Chang ◽  
Jaewan Park ◽  
Chimin Oh ◽  
Chilwoo Lee
Keyword(s):  
Decision Tree ◽  
Real Time ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Recognition Method

scholarly journals Real-Time 3D Hand Gesture Recognition from Depth Image

2013 ◽  
Vol 765-767 ◽  
pp. 2826-2829 ◽  
Author(s):  
Song Lin ◽  
Rui Min Hu ◽  
Yu Lian Xiao ◽  
Li Yu Gong
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Point Cloud ◽  
Hand Gesture Recognition ◽  
Microsoft Kinect ◽  
Depth Image ◽  
Support Vector ◽  
Hand Gesture ◽  
Depth Information ◽  
Moment Invariant

In this paper, we propose a novel real-time 3D hand gesture recognition algorithm based on depth information. We segment out the hand region from depth image and convert it to a point cloud. Then, 3D moment invariant features are computed at the point cloud. Finally, support vector machine (SVM) is employed to classify the shape of hand into different categories. We collect a benchmark dataset using Microsoft Kinect for Xbox and test the propose algorithm on it. Experimental results prove the robustness of our proposed algorithm.

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