Fast vision-based object segmentation for natural landmark detection on indoor mobile robot | |
Chai, Xiaojie; Wen, Feng; Yuan, Kui | |
2011 | |
会议名称 | 2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011 |
会议录名称 | IEEE International Conference on Mechatronics and Automation ( ICMA) |
页码 | 2232-2237 |
会议日期 | 2011 |
会议地点 | Beijing, China |
摘要 | In this paper a new fast vision-based Object Segmentation technique by extracting straight line features from the indoor scenes is proposed. An indoor space scene always contains natural structures like doors, walls, ceilings and floor which have clear straight lines and large homogeneous color surfaces that can be stably detected to form the objects. The objects bounded with lines are very suitable for Indoor Mobile Robot to quickly detect, save as natural landmarks and use in visual SLAM. Compared with the POI (point of interest) features like Harris corner, the line features not only are more robust to changes of scale and illumination, but also can provide more structural information of the indoor environment. This algorithm works in real time and is stable against variation of illumination. The main idea of the method is combining straight lines to form lots of convex polygons. Polygons with homogenous color are kept and adjacent polygons with similar color are merged by a merge test process. A fast line segmentation and fitting method is proposed to improve the line detection efficiency and half edge structure is added to simplify the polygon generation process. Finally experiment results demonstrate the accuracy and robustness of the proposed algorithm in real indoor environments. |
关键词 | Object Segmentation Visual Slam Natural Landmark Indoor Scenes Mobile Robot |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/5239 |
专题 | 智能制造技术与系统研究中心_智能机器人 |
通讯作者 | Chai, Xiaojie |
推荐引用方式 GB/T 7714 | Chai, Xiaojie,Wen, Feng,Yuan, Kui. Fast vision-based object segmentation for natural landmark detection on indoor mobile robot[C],2011:2232-2237. |
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