Evaluation of Embedded Devices for Real-Time Video Lane Detection
[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee
[2.2] Automation, electronics, electrical engineering and space technology
2022
chapter in monograph / paper
english
- lane detection
- embedded systems
- video analysis
- microprocessor power modes
- NVIDIA Jetson
- Raspberry Pi
EN This paper presents a comparison of the performance of embedded systems processing video sequences in real time. As part of the work, practical programs for detecting lanes located on airport areas, which allow autonomous vehicles to move around the airport, were tested. The following modules were used during the tests: Raspberry Pi 4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX. For modules from the NVIDIA Jetson family, the maximum performance of video stream processing depending on the resolution and the selected power mode has been checked. The results of the experiment show that NVIDIA Jetson modules have sufficient computing resources to effectively track lines based on the camera image, even in low power modes.
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