Dynamic Crosswalk Scene Understanding for the Visually Impaired
| Autor: | Lu Zhang, Shishun Tian, Wenbin Zou, Xia Li, Minghuo Zheng |
|---|---|
| Přispěvatelé: | Shenzhen University, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), National Natural Science Foundation of China (NSFC) [61771321, 61871273, 61872429], Key Project of DEGP [2018KCXTD027], Natural Science Foundation of Guangdong Province, China [2020A1515010959], Natural Science Foundation of Shenzhen [JCYJ20200109105832261], Interdisciplinary Innovation Team of Shenzhen University, Université de Nantes (UN)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Nantes Université (NU)-Université de Rennes 1 (UR1) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Visually impaired
Computer science 0206 medical engineering Biomedical Engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Pedestrian blind navigation Image color analysis crosswalk detection Traffic signal [SPI]Engineering Sciences [physics] Global Positioning System 11. Sustainability Internal Medicine Humans Computer vision Pedestrians The visually impaired Audio signal pedestrian traffic light recognition business.industry General Neuroscience Rehabilitation Accidents Traffic object detection Cameras Transforms 020601 biomedical engineering Navigation Roads Vision sensors Key (cryptography) Schema crosswalk Artificial intelligence business Mobile device Visually Impaired Persons |
| Zdroj: | IEEE Transactions on Neural Systems and Rehabilitation Engineering IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29, pp.1478-1486. ⟨10.1109/TNSRE.2021.3096379⟩ IEEE Transactions on Neural Systems and Rehabilitation Engineering, Institute of Electrical and Electronics Engineers, 2021, 29, pp.1478-1486. ⟨10.1109/TNSRE.2021.3096379⟩ |
| ISSN: | 1534-4320 1558-0210 |
| DOI: | 10.1109/TNSRE.2021.3096379⟩ |
| Popis: | International audience; Independent mobility poses a great challenge to the visually impaired individuals. This paper proposes a novel system to understand dynamic crosswalk scenes, which detects the key objects, such as crosswalk, vehicle, and pedestrian, and identifies pedestrian traffic light status. The indication of where and when to cross the road is provided to the visually impaired based on the crosswalk scene understanding. Our proposed system is implemented on a head-mounted mobile device (SensingAI G1) equipped with an Intel RealSense camera and a cellphone, and provides surrounding scene information to visually impaired individuals through audio signal. To validate the performance of the proposed system, we propose a crosswalk scene understanding dataset which contains three sub-datasets: a pedestrian traffic light dataset with 7447 images, a dataset of key objects on the crossroad with 1006 images and a crosswalk dataset with 3336 images. Extensive experiments demonstrated that the proposed system was robust and outperformed the state-of-the-art approaches. The experiment conducted with the visually impaired subjects shows that the system is practical useful. |
| Databáze: | OpenAIRE |
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