Implementation of Motion Detection Methods on Embedded Systems: A Performance Comparison
نویسندگان
چکیده
Recently, deploying machine learning methods and deep models to create an artificial intelligence system has gained huge interest. Several technologies, such as embedded GPU, ARM multicore processors, visual processor units VPUs, tensor TPUs, Field programmable arrays FPGAs, have been developed for this purpose. These processors accelerators fitted on different edge boards single computer SBCs. In work, we present a performance comparison of background subtraction with many video resolutions various technologies boards. The tested are equipped versions GPUs. aim is overcome the lack studies devices compare these recent hardware configurations. implementation was achieved CPUs configuration using OpenCV GPU CUDA OpenCV. Results show that high computational high-resolution videos, four times faster than CPU. For low-mid or resolution, reduced due GPU-CPU bottleneck transfer. This enables reader better choose suitable his mobile application.
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ژورنال
عنوان ژورنال: International Journal of Technology: IJ Tech
سال: 2023
ISSN: ['2087-2100']
DOI: https://doi.org/10.14716/ijtech.v14i3.5950