INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
The area of gesture recognition is changing due to the development of new technology. With the introduction of technologies like the Kinect sensor, there are now more potential for human-computer interaction than with the conventional hand gesture recognition approaches, which are more dependent on gloves and sensors and less adaptable. The aim of working with picture datasets for improved recognition is to extract additional features to improve gesture recognition. It has been noted that adding more characteristics makes it much simpler to accurately recognise hand gestures, and accuracy may also be raised by optimizing the classification process. To improve the performance of the gesture recognition model, enhanced feature extraction and hybrid classification are used in this study.
Keywords:
Hand Gesture, MediaPipe, Gaussian regression, Hybrid classification, Feature extraction
Cite Article:
"Hand Gesture Recognition ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.320 - 324, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211052.pdf
Downloads:
000337070
Publication Details:
Published Paper ID: IJSDR2211052
Registration ID:202528
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 320 - 324
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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