https://scholars.lib.ntu.edu.tw/handle/123456789/500808
Title: | Map Reconstruction for Driving Scenarios Using Monocular Camera: Map Reconstruction for Driving Scenarios | Authors: | Chen, Y.-T. Lin, T.-P. FENG-LI LIAN |
Keywords: | Camera pose estimation; Monocular simultaneous localization and mapping; Nonlinear optimization; Regularization algorithm; Semi-dense map reconstruction | Issue Date: | 2017 | Start page/Pages: | 1045-1046 | Source: | Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 | Abstract: | Environment reconstruction from a monocular camera has been a popular research topic. This technique can be applied to automatic navigation, environment exploration and automatic obstacle avoidance. This paper proposes stereo matching and aims to match the low gradient area around the high gradient area between two images correctly by using the epipolar geometry. The experimental results demonstrate that the proposed regularization algorithm can eliminate most of the noises and reconstruct a more clearly point cloud. © 2017 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040589252&doi=10.1109%2fIIAI-AAI.2017.105&partnerID=40&md5=dedaf4c4050d476465a2b0a5c534321e | DOI: | 10.1109/IIAI-AAI.2017.105 | SDG/Keyword: | Cameras; Nonlinear programming; Optimization; Camera pose estimation; Map reconstruction; Non-linear optimization; Regularization algorithms; Simultaneous localization and mapping; Stereo image processing |
Appears in Collections: | 電機工程學系 |
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