Real-time Implementation of Electromyography for Hand Gesture Detection Using Micro Accelerometer

2016 ◽  
pp. 357-364 ◽  
Author(s):  
Subhendu Roy ◽  
Sraboni Ghosh ◽  
Aratrika Barat ◽  
Madhurima Chattopadhyay ◽  
Debjyoti Chowdhury
Keyword(s):  
Real Time ◽  
Hand Gesture ◽  
Hand Gesture Detection ◽  
Micro Accelerometer

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.

Real-Time Hand Gesture Detection Using Convex Hull and Contour Edge Detection

2021 ◽  
pp. 325-335
Author(s):  
Smriti Amatya ◽  
Ishika ◽  
M. V. Manoj Kumar ◽  
B. S. Prashanth ◽  
H. R. Sneha ◽  
...  
Keyword(s):  
Convex Hull ◽  
Edge Detection ◽  
Real Time ◽  
Hand Gesture ◽  
Hand Gesture Detection

scholarly journals Real-time Hand Gesture Extraction Using Python Programming Language Facilities

2021 ◽  
Vol 39 (6) ◽  
pp. 1031-1040
Author(s):  
Azher A. Fahad ◽  
Hassan J. Hassan ◽  
Salma H. Abdullah
Keyword(s):  
Real Time ◽  
Moving Objects ◽  
Color Space ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Human Contact ◽  
Hand Gesture Detection ◽  
Model Training ◽  
Python Programming ◽  
Hand Area

Hand gesture recognition is one of communication in which used bodily behavior to transmit several messages. This paper aims to detect hand gestures with the mobile device camera and create a customize dataset that used in deep learning model training to recognize hand gestures. The real-time approach was used for all these objectives: the first step is hand area detection; the second step is hand area storing in a dataset form to use in the future for model training. A framework for human contact was put in place by studying pictures recorded by the camera. It was converted the RGB color space image to the greyscale, the blurring method is used for object noise removing efficaciously. To highlight the edges and curves of the hand, the thresholding method is used. And subtraction of complex background is applied to detect moving objects from a static camera. The objectives of the paper were reliable and favorable which helps deaf and dumb people interact with the environment through the sign language fully approved to extract hand movements. Python language as a programming manner to discover hand gestures. This work has an efficient hand gesture detection process to address the problem of framing from real-time video.

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