Gesture Recognition for Enhancing Human Computer Interaction
NOPR - NISCAIR Online Periodicals Repository
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Title |
Gesture Recognition for Enhancing Human Computer Interaction
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Creator |
Chakravarthi, Sangapu Sreenivasa
Rao, B Narendra Kumar Challa, Nagendra Panini Ranjana, R Rai, Ankush |
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Subject |
Extreme learning
Finger tracking Hand gesture Motion detection Voice commands |
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Description |
438-443
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 |
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Date |
2023-04-03T09:56:54Z
2023-04-03T09:56:54Z 2023-04 |
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Type |
Article
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Identifier |
0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61653 https://doi.org/10.56042/jsir.v82i04.72387 |
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Language |
en
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Publisher |
NIScPR-CSIR,India
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Source |
JSIR Vol.82(04) [April 2023]
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