Katon: real-time hand-gesture recognition on tiny embedded systems

Katon: real-time hand-gesture recognition on tiny embedded systems

As gesture recognition technology transforms human-computer interactions across various applications such as Virtual Reality (VR) and other smart wearables, the demand for real-time gesture recognition on limited-capacity hardware increases. Most of these applications need efficiency and responsi...

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Bibliographic Details
Main Author: Mohamed Ali Mohamed Umar
Other Authors: Mohamed M. Sabry Aly
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Computer and Information Science
Engineering
Hand-gesture
Arrtificial intelliigence
Deep learning
Embedded devices
Recognition
Online Access:https://hdl.handle.net/10356/181208
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Institution: Nanyang Technological University
Language: English
Description
Summary:As gesture recognition technology transforms human-computer interactions across various applications such as Virtual Reality (VR) and other smart wearables, the demand for real-time gesture recognition on limited-capacity hardware increases. Most of these applications need efficiency and responsiveness, which highlights the importance of research in lightweight algorithms capable of real-time processing in resource limited areas. This study evaluates various lightweight algorithms for their viability in real-time hand gesture recognition on resource-limited hardware, focusing on the Himax WE-I Development Board.

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