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Gesture Recognition for Enhancing Human Computer Interaction


Affiliations
1 Department of CSE, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai 601 103, India
2 AIML, School of Computing, Mohan Babu University, Tirupati 517 102, India
3 School of Computer Science and Engineering, VIT-AP University, Amaravati 522 237, India
4 Department of IT, Sri Sairam Engineering College, Chennai– 600 044, India
5 AI Division, Faculty of Electronics and Information Technology, Warsaw University of Technology, 00-661 Warsaw, Poland
 

Gesture recognition is critical in human-computer communication. As observed, a plethora of current technological developments are in the works, including biometric authentication, which we see all the time in our smartphones. Hand gesture focus, a frequent human-computer interface in which we manage our devices by presenting our hands in front of a webcam, can benefit people of different backgrounds. Some of the efforts in human-computer interface include voice assistance and virtual mouse implementation with voice commands, fingertip recognition and hand motion tracking based on an image in a live video. Human Computer Interaction (HCI), particularly vision-based gesture and object recognition, is becoming increasingly important. Hence, we focused to design and develop a system for monitoring fingers using extreme learning-based hand gesture recognition techniques. Extreme learning helps in quickly interpreting the hand gestures with improved accuracy which would be a highly useful in the domains like healthcare, financial transactions and global business.

Keywords

Extreme Learning, Finger Tracking, Hand Gesture, Motion Detection, Voice Commands.
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  • Gesture Recognition for Enhancing Human Computer Interaction

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Authors

Sangapu Sreenivasa Chakravarthi
Department of CSE, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai 601 103, India
B Narendra Kumar Rao
AIML, School of Computing, Mohan Babu University, Tirupati 517 102, India
Nagendra Panini v
School of Computer Science and Engineering, VIT-AP University, Amaravati 522 237, India
R Ranjana
Department of IT, Sri Sairam Engineering College, Chennai– 600 044, India
Ankush Rai
AI Division, Faculty of Electronics and Information Technology, Warsaw University of Technology, 00-661 Warsaw, Poland

Abstract


Gesture recognition is critical in human-computer communication. As observed, a plethora of current technological developments are in the works, including biometric authentication, which we see all the time in our smartphones. Hand gesture focus, a frequent human-computer interface in which we manage our devices by presenting our hands in front of a webcam, can benefit people of different backgrounds. Some of the efforts in human-computer interface include voice assistance and virtual mouse implementation with voice commands, fingertip recognition and hand motion tracking based on an image in a live video. Human Computer Interaction (HCI), particularly vision-based gesture and object recognition, is becoming increasingly important. Hence, we focused to design and develop a system for monitoring fingers using extreme learning-based hand gesture recognition techniques. Extreme learning helps in quickly interpreting the hand gestures with improved accuracy which would be a highly useful in the domains like healthcare, financial transactions and global business.

Keywords


Extreme Learning, Finger Tracking, Hand Gesture, Motion Detection, Voice Commands.

References