TY - GEN
T1 - Real Time Hand Gesture Recognition Using Leap Motion Controller Based on CNN-SVM Architechture
AU - Ikram, Aamrah
AU - Liu, Yue
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/20
Y1 - 2021/5/20
N2 - In rapidly growing field of Artificial Intelligence (AI), Hand Gesture Recognition (HGR) is an important entity. In the real world system it is very challenging to detect and classify Dynamic Hand Gestures (DHG). As there is considerable diversity in gesture performed by individuals and the system should be real time to overcome the delay between performing and classifying the gesture. In this work, we proposed a new approach for efficient HGR using Convolutional Neural Network (CNN) along with Support Vector Machine (SVM) classifier. CNN used to avoid feature extraction and to minimized the number of trained parameters. However, to reduce the error, Error Break Propagation Algorithm (EBPA) is implemented. For the system's validity and robustness SVM optimizer has been used. An overall accuracy of 93 % has achieved on DHG 14/28 dataset.
AB - In rapidly growing field of Artificial Intelligence (AI), Hand Gesture Recognition (HGR) is an important entity. In the real world system it is very challenging to detect and classify Dynamic Hand Gestures (DHG). As there is considerable diversity in gesture performed by individuals and the system should be real time to overcome the delay between performing and classifying the gesture. In this work, we proposed a new approach for efficient HGR using Convolutional Neural Network (CNN) along with Support Vector Machine (SVM) classifier. CNN used to avoid feature extraction and to minimized the number of trained parameters. However, to reduce the error, Error Break Propagation Algorithm (EBPA) is implemented. For the system's validity and robustness SVM optimizer has been used. An overall accuracy of 93 % has achieved on DHG 14/28 dataset.
KW - convolution neural network
KW - dynamic hand gesture
KW - support vector machine
KW - virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85111447661&partnerID=8YFLogxK
U2 - 10.1109/ICVR51878.2021.9483844
DO - 10.1109/ICVR51878.2021.9483844
M3 - Conference contribution
AN - SCOPUS:85111447661
T3 - International Conference on Virtual Rehabilitation, ICVR
SP - 5
EP - 9
BT - 2021 IEEE 7th International Conference on Virtual Reality, ICVR 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Conference on Virtual Reality, ICVR 2021
Y2 - 20 May 2021 through 22 May 2021
ER -