{"title":"Some improvements in the RGB-D SLAM system","authors":"Hieu Pham Quang, N. Ly","doi":"10.1109/RIVF.2015.7049884","DOIUrl":null,"url":null,"abstract":"RGB-D cameras offer both color and depth images of the surrounding environment, making them an attractive option for robot sensor. In this work, we present an RGB-D SLAM system using the Microsoft Kinect. The proposed system is a full 6DoF (Degrees of Freedom) SLAM system which can estimate camera trajectory and reconstruct a 3D model of the environment in real-time. Unlike traditional filtering-based approaches, our system optimizes the entire trajectory by the use of graph optimization. We achieve better accuracy than a previous system by employing key-frame matching instead of frame-to-frame matching. We evaluate our system on a published dataset. The results demonstrate that our system can handle unrestricted camera movements in indoor settings.","PeriodicalId":166971,"journal":{"name":"The 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIVF.2015.7049884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

RGB-D cameras offer both color and depth images of the surrounding environment, making them an attractive option for robot sensor. In this work, we present an RGB-D SLAM system using the Microsoft Kinect. The proposed system is a full 6DoF (Degrees of Freedom) SLAM system which can estimate camera trajectory and reconstruct a 3D model of the environment in real-time. Unlike traditional filtering-based approaches, our system optimizes the entire trajectory by the use of graph optimization. We achieve better accuracy than a previous system by employing key-frame matching instead of frame-to-frame matching. We evaluate our system on a published dataset. The results demonstrate that our system can handle unrestricted camera movements in indoor settings.
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RGB-D SLAM系统的一些改进
RGB-D相机提供周围环境的彩色和深度图像,使其成为机器人传感器的一个有吸引力的选择。在这项工作中,我们提出了一个使用微软Kinect的RGB-D SLAM系统。所提出的系统是一个全6DoF(自由度)SLAM系统,可以估计相机轨迹并实时重建环境的3D模型。与传统的基于过滤的方法不同,我们的系统通过使用图优化来优化整个轨迹。通过采用关键帧匹配代替帧对帧匹配,我们获得了比以前系统更好的精度。我们在发布的数据集上评估我们的系统。结果表明,该系统可以处理室内环境下不受限制的摄像机运动。
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