Proposing Gesture Recognition Algorithm Using HOG and SVM for Smart-Home Applications

2021 ◽  
pp. 315-323
Author(s):  
Phat Nguyen Huu ◽  
Tan Phung Ngoc ◽  
Hoang Tran Manh
Keyword(s):  
Gesture Recognition ◽  
Smart Home ◽  
Recognition Algorithm

scholarly journals Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3937
Author(s):  
Seungeon Song ◽  
Bongseok Kim ◽  
Sangdong Kim ◽  
Jonghun Lee
Keyword(s):  
Deep Learning ◽  
Gesture Recognition ◽  
Smart Home ◽  
Doppler Radar ◽  
Radar Images ◽  
Radar Signature ◽  
Memory Efficiency ◽  
High Compression ◽  
Value Decomposition ◽  
Deep Learning Model

Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar’s inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.

An sEMG Gesture Recognition Algorithm Based on Improved MobileNet

2021 ◽  
Author(s):  
Peiyu Liu ◽  
Jian Guo ◽  
Jiemin Lu ◽  
Jingwen Wang ◽  
Shulong Dong ◽  
...  
Keyword(s):  
Gesture Recognition ◽  
Recognition Algorithm
Sign in / Sign up

Export Citation Format

Share Document