Please use this identifier to cite or link to this item: https://doi.org/10.3390/s140509046
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dc.titleRobust curb detection with fusion of 3d-Lidar and camera data
dc.contributor.authorTan, J.
dc.contributor.authorLi, J.
dc.contributor.authorAn, X.
dc.contributor.authorHe, H.
dc.date.accessioned2016-06-03T08:08:02Z
dc.date.available2016-06-03T08:08:02Z
dc.date.issued2014-05-21
dc.identifier.citationTan, J., Li, J., An, X., He, H. (2014-05-21). Robust curb detection with fusion of 3d-Lidar and camera data. Sensors (Switzerland) 14 (5) : 9046-9073. ScholarBank@NUS Repository. https://doi.org/10.3390/s140509046
dc.identifier.issn14248220
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/125101
dc.description.abstractCurb detection is an essential component of Autonomous Land Vehicles (ALV), especially important for safe driving in urban environments. In this paper, we propose a fusion-based curb detection method through exploiting 3D-Lidar and camera data. More specifically, we first fuse the sparse 3D-Lidar points and high-resolution camera images together to recover a dense depth image of the captured scene. Based on the recovered dense depth image, we propose a filter-based method to estimate the normal direction within the image. Then, by using the multi-scale normal patterns based on the curb's geometric property, curb point features fitting the patterns are detected in the normal image row by row. After that, we construct a Markov Chain to model the consistency of curb points which utilizes the continuous property of the curb, and thus the optimal curb path which links the curb points together can be efficiently estimated by dynamic programming. Finally, we perform post-processing operations to filter the outliers, parameterize the curbs and give the confidence scores on the detected curbs. Extensive evaluations clearly show that our proposed method can detect curbs with strong robustness at real-time speed for both static and dynamic scenes. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.3390/s140509046
dc.sourceScopus
dc.subject3D-lidar
dc.subjectCamera
dc.subjectCurb detection
dc.subjectDepth image
dc.subjectFusion
dc.subjectMarkov chain
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.3390/s140509046
dc.description.sourcetitleSensors (Switzerland)
dc.description.volume14
dc.description.issue5
dc.description.page9046-9073
dc.identifier.isiut000337112200076
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