ASIA unversity:Item 310904400/8851
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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8851


    Title: Vision-based nighttime vehicle detection and range estimation for driver assistance
    Authors: Chen, Yen-Lin;Lin, Chuan-Tsai;Fan, Chung-Jui;Hsieh, Chih-Ming;Wu, Bing-Fei
    Contributors: Department of Computer Science and Information Engineering
    Keywords: Control theory;Cybernetics;Digital image storage;Image segmentation;Machinery;Security systems;Vehicles;Autonomous vehicles;Control strategies;Detection and tracking;Driver assistance;In-vehicle;Nighttime driving;Object segmentation;Pattern analysis;Range estimation;Real time traffics;Real time vision;Recording evidence;Traffic accidents;Traffic conditions;Urban environments;Vehicle detection;Video surveillance;Vision based
    Date: 2008
    Issue Date: 2010-04-08 12:22:29 (UTC+0)
    Publisher: Asia University
    Abstract: This paper presents a real-time vision system for assisting driver during nighttime driving. The proposed system provides the following features: 1) Effectively detection and tracking of oncoming and preceding vehicles based on image segmentation and pattern analysis techniques. 2) Robust and adaptive vehicle detection under various illuminated conditions at nighttime urban environments benefited by a novel automatic object segmentation scheme. 3) Providing beneficial information for assisting the driver to perceive surrounding traffic conditions outside the car during nighttime driving. 4) Providing a versatile control strategy for in-vehicle facilities of the autonomous vehicles. 5) Offering real-time traffic event-driven video surveillance machinery for recording evidences of possible traffic accidents. Experimental results demonstrate the feasibility and effectiveness of the proposed system on nighttime driver assistance issues. © 2008 IEEE.
    Relation: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics :2988-2993
    Appears in Collections:[Department of Computer Science and Information Engineering] Proceedings

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