Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network
Along with society’s development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/6/3329 |
| _version_ | 1797608960559153152 |
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| author | Leyre Encío César Díaz Carlos R. del-Blanco Fernando Jaureguizar Narciso García |
| author_facet | Leyre Encío César Díaz Carlos R. del-Blanco Fernando Jaureguizar Narciso García |
| author_sort | Leyre Encío |
| collection | DOAJ |
| description | Along with society’s development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an accident and the carbon footprint, and negatively affecting the driver’s health. Therefore, technological resources to deal with parking management and real-time monitoring have become key players in this scenario to speed up the parking process in urban areas. This work proposes a new computer-vision-based system that detects vacant parking spaces in challenging situations using color imagery processed by a novel deep-learning algorithm. This is based on a multi-branch output neural network that maximizes the contextual image information to infer the occupancy of every parking space. Every output infers the occupancy of a specific parking slot using all the input image information, unlike existing approaches, which only use a neighborhood around every slot. This allows it to be very robust to changing illumination conditions, different camera perspectives, and mutual occlusions between parked cars. An extensive evaluation has been performed using several public datasets, proving that the proposed system outperforms existing approaches. |
| first_indexed | 2024-03-11T05:54:59Z |
| format | Article |
| id | doaj.art-0ec0124afe404798a0b924bf81beae46 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:54:59Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0ec0124afe404798a0b924bf81beae462023-11-17T13:49:10ZengMDPI AGSensors1424-82202023-03-01236332910.3390/s23063329Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt NetworkLeyre Encío0César Díaz1Carlos R. del-Blanco2Fernando Jaureguizar3Narciso García4Grupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, SpainGrupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, SpainGrupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, SpainGrupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, SpainGrupo de Tratamiento de Imágenes (GTI), Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, SpainAlong with society’s development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an accident and the carbon footprint, and negatively affecting the driver’s health. Therefore, technological resources to deal with parking management and real-time monitoring have become key players in this scenario to speed up the parking process in urban areas. This work proposes a new computer-vision-based system that detects vacant parking spaces in challenging situations using color imagery processed by a novel deep-learning algorithm. This is based on a multi-branch output neural network that maximizes the contextual image information to infer the occupancy of every parking space. Every output infers the occupancy of a specific parking slot using all the input image information, unlike existing approaches, which only use a neighborhood around every slot. This allows it to be very robust to changing illumination conditions, different camera perspectives, and mutual occlusions between parked cars. An extensive evaluation has been performed using several public datasets, proving that the proposed system outperforms existing approaches.https://www.mdpi.com/1424-8220/23/6/3329parkingdetectionparking lotconvolutional neural networksConvNeXtdeep learning |
| spellingShingle | Leyre Encío César Díaz Carlos R. del-Blanco Fernando Jaureguizar Narciso García Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network Sensors parking detection parking lot convolutional neural networks ConvNeXt deep learning |
| title | Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network |
| title_full | Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network |
| title_fullStr | Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network |
| title_full_unstemmed | Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network |
| title_short | Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network |
| title_sort | visual parking occupancy detection using extended contextual image information via a multi branch output convnext network |
| topic | parking detection parking lot convolutional neural networks ConvNeXt deep learning |
| url | https://www.mdpi.com/1424-8220/23/6/3329 |
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