Detection of Dangerous Situations Near Pedestrian Crossings using In-Car Camera

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dc.contributor.authorKubanek, Mariusz
dc.contributor.authorKarbowiak, Lukasz
dc.contributor.authorBobulski, Janusz
dc.contributor.editorSkala, Václav
dc.date.accessioned2023-10-18T17:48:53Z
dc.date.available2023-10-18T17:48:53Z
dc.date.issued2023
dc.description.abstract-translatedThe paper presents a method for detecting dangerous situations near pedestrian crossings using an in-car camera system. The approach utilizes deep learning-based object detection to identify pedestrians and vehicles, analyzing their behavior to identify potential hazards. The system incorporates vehicle sensor data for enhanced accuracy. Evaluation results show high accuracy in detecting dangerous situations. The proposed system can potentially enhance pedestrian and driver safety in urban transportation.en
dc.description.sponsorshipe project financed under the program of the Pol ish Minister of Science and Higher Education under the name "Regional Initiative of Excellence" in the years 2019 - 2023 project number 020/RID/2018/19 the amount of financing PLN 12,000,000en
dc.format4 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationWSCG 2023: full papers proceedings: 1. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 393-396.en
dc.identifier.doihttps://www.doi.org/10.24132/CSRN.3301.41
dc.identifier.isbn978-80-86943-32-9
dc.identifier.issn2464–4617 (print)
dc.identifier.issn2464–4625 (CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/54449
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.rights.accessopenAccessen
dc.subjectdetekce objektucs
dc.subjecthluboké učenícs
dc.subjectautonomní systémycs
dc.subject.translatedobject detectionen
dc.subject.translateddeep learningen
dc.subject.translatedautonomous systemsen
dc.titleDetection of Dangerous Situations Near Pedestrian Crossings using In-Car Cameraen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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