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Titlebook: Computer Vision for Driver Assistance; Simultaneous Traffic Mahdi Rezaei,Reinhard Klette Book 2017 Springer International Publishing AG 201

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發(fā)表于 2025-3-21 18:14:48 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Computer Vision for Driver Assistance
副標(biāo)題Simultaneous Traffic
編輯Mahdi Rezaei,Reinhard Klette
視頻videohttp://file.papertrans.cn/235/234078/234078.mp4
概述Explores theoretical and practical aspects of driver assistance systems, illustrated by various real-world experiments.Presents technically advanced concepts in an accessible way that is suitable for
叢書(shū)名稱(chēng)Computational Imaging and Vision
圖書(shū)封面Titlebook: Computer Vision for Driver Assistance; Simultaneous Traffic Mahdi Rezaei,Reinhard Klette Book 2017 Springer International Publishing AG 201
描述.This book summarises the state of the art in computer vision-based driver and road monitoring, focussing on monocular vision technology in particular, with the aim to address challenges of driver assistance and autonomous driving systems..While the systems designed for the assistance of drivers of on-road vehicles are currently converging to the design of autonomous vehicles, the research presented here focuses on scenarios where a driver is still assumed to pay attention to the traffic while operating a partially automated vehicle. Proposing various computer vision algorithms, techniques and methodologies, the authors also provide a general review of computer vision technologies that are relevant for driver assistance and fully autonomous vehicles..Computer Vision for Driver Assistance. is the first book of its kind and will appeal to undergraduate and graduate students, researchers, engineers and those generally interested in computer vision-related topics inmodern vehicle design.?.
出版日期Book 2017
關(guān)鍵詞advanced driver-assistance systems; autonomous vehicles; driver distraction; driver fatigue; vehicle det
版次1
doihttps://doi.org/10.1007/978-3-319-50551-0
isbn_softcover978-3-319-84426-8
isbn_ebook978-3-319-50551-0Series ISSN 1381-6446
issn_series 1381-6446
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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Samuel H. Preston,Irma T. Elo,Ira Rosenwaikele at all times, but provided automated control features of the vehicle (based on input data generated by different sensors) already enhance safety and driver comfort. We especially consider automated control features possible by using camera data.
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https://doi.org/10.1007/978-90-481-8978-6ised and unsupervised learning approaches. The chapter provides technical details for each method, discussions on the strengths and weaknesses of each method, and gives examples and various applications for each method. Material is provided to support a decision for an appropriate object detection t
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Data Sources for Health Demography,g method and an accurate 2D-to-3D registration technique to obtain the driver’s head pose, yawing detection, and head-nodding detection. Chapter . and this chapter present the first major objective of this book’s focus on “driver behaviour” (i.e. driver drowsiness and distraction detection). The fin
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https://doi.org/10.1007/978-3-319-50551-0advanced driver-assistance systems; autonomous vehicles; driver distraction; driver fatigue; vehicle det
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