Energy-efficient real-time computer vision applications in practice

Mark A. M. Kramer; Peter M. Roth

doi:10.1117/12.3025261

20 June 2024 Energy-efficient real-time computer vision applications in practice

Mark A. M. Kramer, Peter M. Roth

Proceedings Volume 13000, Real-time Processing of Image, Depth, and Video Information 2024; 1300006 (2024) https://doi.org/10.1117/12.3025261
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

For many practical applications, we face the problem that computer vision systems must be installed in the wild, without or with a limited permanent power supply. Therefore, computationally and energy efficient solutions are needed. In particular, in this work, we show that the meaningful use of single-board computers (SBCs) can help achieve these goals. This is in line with the goals of Green AI. In particular, we show that the computer vision algorithms adopted on SBCs yield competitive results compared to high-performance computing devices. To this end, in addition to quantitative performance evaluations, we also measured and compared the power consumption of the algorithmic and technical setup used for various practical problems. These examples demonstrate the practical sustainability of SBCs. They show their performance, reduced power consumption, and lower environmental impact, while still providing real-time performance.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mark A. M. Kramer and Peter M. Roth "Energy-efficient real-time computer vision applications in practice", Proc. SPIE 13000, Real-time Processing of Image, Depth, and Video Information 2024, 1300006 (20 June 2024); https://doi.org/10.1117/12.3025261

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