Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/4092
Title: MediaPipe with LSTM Architecture for Real-Time Hand Gesture Recognization
Authors: Biswas, Sougatamoy
Nandy, Anup
Naskar, Asim Kumar
Saw, Rahul
Keywords: Gesture recognition
LSTM
MediaPipe
Human-computer interaction
Issue Date: Nov-2023
Citation: 8th International Conference On Computer Vision and Image Processing (CVIP) 2023 At IIT Jammu During 3rd -5th November 2023
Abstract: Gesture recognition plays a vital role in the area of research for human-computer interaction (HCI). The integration of MediaPipe with Long Short Term Memory (LSTM) architecture holds tremendous potential for real-time hand gesture recognition. MediaPipe provides a robust and versatile framework for capturing and processing multimedia input, such as video streams from cameras or pre-recorded video files. The temporal modeling capabilities of LSTM captures the temporal dynamics of hand gestures. This research paper aims to present a novel method utilizing the MediaPipe with LSTM architecture for real-time hand gesture recognition. A test on real-time gesture recognition is performed to evaluate the performance of the suggested model. Our results demonstrate that the suggested method outperforms other state-of-theart approaches on our custom made dataset with an accuracy of 98.99%.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/4092
Appears in Collections:Conference Papers

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