Lane detection and spatiotemporal reconstruction using the macroblock predictions method
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Document Type
Article
Source Title
Journal of Advanced Computational Intelligence and Intelligent Informatics
Volume
22
Issue
5
First Page
660
Last Page
665
Publication Date
9-1-2018
Abstract
Detection and tracking of road lane markings offers several applications in intelligent transport systems (ITS). Although it is perceived as the simple task of isolating lanes on various types of roads, the accuracy of detection remains an issue. Several studies in recent literature have proposed solutions to this problem; however, none of these have used the method of macroblock (MB) prediction. This paper focuses on the type of MB applied for lane detection, tracking, and predictions, as well as the trade-off between the accuracy and complexity of implementing the system. This study makes the following contributions: (1) best MB for spatiotemporal lane detection and reconstruction; (2) best function approximation for lane predictions; and (3) best MB in terms of performance under different conditions. © 2018 Fuji Technology Press.All Rights Reserved.
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Digitial Object Identifier (DOI)
10.20965/jaciii.2018.p0660
Recommended Citation
Roxas, E. A., Vicerra, R. P., Santos, G. C., Dadios, E. P., & Bandala, A. A. (2018). Lane detection and spatiotemporal reconstruction using the macroblock predictions method. Journal of Advanced Computational Intelligence and Intelligent Informatics, 22 (5), 660-665. https://doi.org/10.20965/jaciii.2018.p0660
Disciplines
Mechanical Engineering
Keywords
Intelligent transportation systems; Computer vision; Lane lines (Roads); Automatic tracking
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