Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/4092
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Biswas, Sougatamoy | - |
dc.contributor.author | Nandy, Anup | - |
dc.contributor.author | Naskar, Asim Kumar | - |
dc.contributor.author | Saw, Rahul | - |
dc.date.accessioned | 2023-11-16T12:37:19Z | - |
dc.date.available | 2023-11-16T12:37:19Z | - |
dc.date.issued | 2023-11 | - |
dc.identifier.citation | 8th International Conference On Computer Vision and Image Processing (CVIP) 2023 At IIT Jammu During 3rd -5th November 2023 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/4092 | - |
dc.description | Copyright belongs to proceeding publisher | en_US |
dc.description.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%. | en_US |
dc.subject | Gesture recognition | en_US |
dc.subject | LSTM | en_US |
dc.subject | MediaPipe | en_US |
dc.subject | Human-computer interaction | en_US |
dc.title | MediaPipe with LSTM Architecture for Real-Time Hand Gesture Recognization | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
2023_CVIP_SBiswas_MediaPipe.pdf | 510.74 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.