Vol. 2 No. 1 (2022): Issue 2
Articles

Real-Time 3D Model Reconstruction through Energy-Efficient Edge Computing

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  • Hanrui Yan
Hanrui Yan
ASCENDING inc
DOI: https://doi.org/10.71070/oaml.v2i1.48

Published 2022-10-18

Keywords

  • Real-time 3D Model Reconstruction,
  • Virtual Reality,
  • Edge Computing,
  • Computational Efficiency,
  • Advanced Algorithms

How to Cite

Yan, H. (2022). Real-Time 3D Model Reconstruction through Energy-Efficient Edge Computing. Optimizations in Applied Machine Learning, 2(1). https://doi.org/10.71070/oaml.v2i1.48
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

Real-time 3D model reconstruction plays a vital role in various fields such as virtual reality, robotics, and environmental monitoring. As the demand for efficient and accurate reconstruction increases, the reliance on edge computing for real-time processing becomes crucial. However, current research faces challenges in balancing computational efficiency and model accuracy. This paper addresses these challenges by proposing a novel approach to real-time 3D model reconstruction through energy-efficient edge computing. The innovation lies in optimizing computational resources at the edge to enhance reconstruction speed without compromising model quality. By integrating advanced algorithms and edge computing techniques, this work aims to significantly improve the efficiency and accuracy of real-time 3D model reconstruction, paving the way for broader applications in diverse domains.

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