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Dynamic objects elimination in SLAM based on image fusion

机译:基于图像融合的SLAM动态对象消除

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In the process of vision-based simultaneous localization and mapping (SLAM), if there is a moving object entering the view field of the camera, a trajectory of the object will be preserved in the constructed point cloud map. However, the other types of maps converted from the point cloud maps cannot be directly used for navigation. This paper studies the dynamic objects elimination in SLAM based on image fusion algorithm. First, we construct a camera motion model for the moving platform. Then, the camera motion is decomposed into two parts: translation and rotation, two constrains were proposed to locate the dynamic regions. Finally, these dynamic regions in the image sequence are set to blank, while we choose one of the image planes as the projection plane, and map the information of other images to the plane to get a fusion image. The results contain all environment information, and the fusion image can be used to replace the image sequence in SLAM. Experiment results demonstrate that our method can eliminate the influence of the dynamic objects effectively. (C) 2018 Elsevier B.V. All rights reserved.
机译:在基于视觉的同时定位和地图绘制(SLAM)过程中,如果有移动物体进入相机的视野,则该物体的轨迹将保留在构造的点云图中。但是,从点云地图转换而来的其他类型的地图不能直接用于导航。本文研究了基于图像融合算法的SLAM中动态目标的消除方法。首先,我们为移动平台构建摄像机运动模型。然后,将摄像机的运动分解为两个部分:平移和旋转,并提出了两个约束条件来定位动态区域。最后,将图像序列中的这些动态区域设置为空白,同时我们选择其中一个图像平面作为投影平面,并将其他图像的信息映射到该平面以获得融合图像。结果包含所有环境信息,融合图像可用于替换SLAM中的图像序列。实验结果表明,该方法可以有效消除动态物体的影响。 (C)2018 Elsevier B.V.保留所有权利。

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