Vision-based Parking Occupation Detecting with Embedded AI Processor
| Autor: | Seung Eun Lee, Kwon Neung Cho, Hyun Woo Oh |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Measure (data warehouse)
Training set Vision based Computer science business.industry 020208 electrical & electronic engineering Real-time computing Cognitive neuroscience of visual object recognition Byte 020206 networking & telecommunications 02 engineering and technology GeneralLiterature_MISCELLANEOUS Fisheye lens Software 0202 electrical engineering electronic engineering information engineering business Software measurement |
| Zdroj: | ICCE |
| DOI: | 10.1109/icce50685.2021.9427661 |
| Popis: | Recently, as the interest of smart parking system is increasing, the various methods for detecting parking occupation are under study. In this paper, we present a vision-based parking occupation detection with embedded AI processor. By employing a fisheye lens camera, multiple parking slot states are identified in one device. We measure the recognition rate of the AI processor in the proposed system and determine the optimized configuration with software simulator. The highest recognition rate is measured at 94.48% in the configuration of 64 number of training data with 256 bytes data size. |
| Databáze: | OpenAIRE |
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