Real-Time Hand Gesture Detection and Recognition by Random Forest

2012 ◽  
pp. 747-755 ◽  
Author(s):  
Xian Zhao ◽  
Zhan Song ◽  
Jian Guo ◽  
Yanguo Zhao ◽  
Feng Zheng
Keyword(s):  
Random Forest ◽  
Real Time ◽  
Hand Gesture ◽  
Hand Gesture Detection ◽  
Detection And Recognition

Real-Time Gesture Recognition for Controlling a Virtual Hand

2012 ◽  
Vol 463-464 ◽  
pp. 1147-1150 ◽  
Author(s):  
Constantin Catalin Moldovan ◽  
Ionel Staretu
Keyword(s):  
Virtual Environments ◽  
Real Time ◽  
Three Dimensional ◽  
Video Stream ◽  
Human Hand ◽  
Hand Motion ◽  
Virtual Hand ◽  
Hand Control ◽  
Hand Gesture Detection ◽  
Detection And Recognition

Object tracking in three dimensional environments is an area of research that has attracted a lot of attention lately, for its potential regarding the interaction between man and machine. Hand gesture detection and recognition, in real time, from video stream, plays a significant role in the human-computer interaction and, on the current digital image processing applications, this represent a difficult task. This paper aims to present a new method for human hand control in virtual environments, by eliminating the need of an external device currently used for hand motion capture and digitization. A first step in this direction would be the detection of human hand, followed by the detection of gestures and their use to control a virtual hand in a virtual environment.

Real-Time 3D Hand Gesture Detection from Depth Images

2013 ◽  
Vol 756-759 ◽  
pp. 4138-4142 ◽  
Author(s):  
Lin Song ◽  
Rui Min Hu ◽  
Hua Zhang ◽  
Yu Lian Xiao ◽  
Li Yu Gong
Keyword(s):  
Real Time ◽  
Time Algorithm ◽  
State Machine ◽  
Microsoft Kinect ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Depth Images ◽  
Frame Difference ◽  
Effectiveness And Efficiency ◽  
Hand Gesture Detection

In this paper, we describe an real-time algorithm to detect 3D hand gestures from depth images. Firstly, we detect moving regions by frame difference; then, regions are refined by removing small regions and boundary regions; finally, foremost region is selected and its trajectories are classified using an automatic state machine. Experiments on Microsoft Kinect for Xbox captured sequences show the effectiveness and efficiency of our system.

Sign in / Sign up

Export Citation Format

Share Document