PhyCV: The First Physics-inspired Computer Vision Library

التفاصيل البيبلوغرافية
العنوان: PhyCV: The First Physics-inspired Computer Vision Library
المؤلفون: Zhou, Yiming, MacPhee, Callen, Suthar, Madhuri, Jalali, Bahram
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
الوصف: PhyCV is the first computer vision library which utilizes algorithms directly derived from the equations of physics governing physical phenomena. The algorithms appearing in the current release emulate, in a metaphoric sense, the propagation of light through a physical medium with natural and engineered diffractive properties followed by coherent detection. Unlike traditional algorithms that are a sequence of hand-crafted empirical rules or deep learning algorithms that are usually data-driven and computationally heavy, physics-inspired algorithms leverage physical laws of nature as blueprints for inventing algorithms. PhyCV features low-dimensionality and high- efficiency, making it ideal for edge computing applications. We demonstrate real-time video processing on NVIDIA Jetson Nano using PhyCV. In addition, these algorithms have the potential to be implemented in real physical devices for fast and efficient computation in the form of analog computing. The open-sourced code is available at https://github.com/JalaliLabUCLA/phycv
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2301.12531
رقم الأكسشن: edsarx.2301.12531
قاعدة البيانات: arXiv