完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.author | Tseng, Shih-Huan | |
dc.contributor.author | Peng, Yu-An | |
dc.contributor.author | Yu, Jia-Yuan | |
dc.contributor.author | Fu, Li-Chen | |
dc.contributor.author | Wang, Shyh-Roei | |
dc.date.accessioned | 2011-03-31T22:54:38Z | |
dc.date.accessioned | 2020-05-18T03:22:28Z | - |
dc.date.available | 2011-03-31T22:54:38Z | |
dc.date.available | 2020-05-18T03:22:28Z | - |
dc.date.issued | 2011-03-31T22:54:38Z | |
dc.date.submitted | 2009-11-27 | |
dc.identifier.uri | http://dspace.lib.fcu.edu.tw/handle/2377/30233 | - |
dc.description.abstract | In this paper, we propose a method to make the mobile robots building a vision-based hierarchical map and then quickly localizing itself by this map. The top-level map is a topological map which consists of “Places”. Topological map is represented through the graph and suitable for the large-scale environments. In this map, the vertices comprise some visual information for efficiently and robustly identifying the “Places” of the robot’s environment and the edges denote the spatial rela-tion between these “Places”. The visual information con-sists of the characteristics of segments and SIFT features. The former indexes “Place” coarsely and the latter is with the capability of indentifying the position within the cur-rent Place finely. When localizing itself, we merely com-pute the similarity by voting corresponding SIFT features between current information and the vertices indexed with the similar characterization of segments. This locali-zation is efficient because of the low time complexity of characterization of segments and the few candidates of the sets of SIFT features. In the other aspect, the scale, orien-tation and illumination invariant of SIFT features make this localization robust. | |
dc.description.sponsorship | National Taipei University,Taipei | |
dc.format.extent | 7p. | |
dc.relation.ispartofseries | NCS 2009 | |
dc.subject | monocular | |
dc.subject | vision | |
dc.subject | global localization | |
dc.subject | in-door | |
dc.subject | hierarchical | |
dc.subject.other | Workshop on Image Processing, Computer Graphics, and Multimedia Technologies | |
dc.title | Vision-based Global Localization of Large-Scale Indoor Environments with Hierarchical Map | |
分類: | 2009年 NCS 全國計算機會議 |
文件中的檔案:
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ICM 1-3.pdf | 480.9 kB | Adobe PDF | 檢視/開啟 |
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