Toward Efficient 3-D Colored Mapping in GPS-/GNSS-Denied Environments

التفاصيل البيبلوغرافية
العنوان: Toward Efficient 3-D Colored Mapping in GPS-/GNSS-Denied Environments
المؤلفون: Yuhan Lian, Chenglu Wen, Jonathan Li, Cheng Wang, Jinbin Tan, Yan Xia, Yudi Dai
المصدر: IEEE Geoscience and Remote Sensing Letters. 17:147-151
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE), 2020.
سنة النشر: 2020
مصطلحات موضوعية: Laser scanning, business.industry, Computer science, Calibration (statistics), ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 0211 other engineering and technologies, Point cloud, Ranging, 02 engineering and technology, Simultaneous localization and mapping, Geotechnical Engineering and Engineering Geology, Lidar, Global Positioning System, Computer vision, Artificial intelligence, Electrical and Electronic Engineering, business, 021101 geological & geomatics engineering, Camera resectioning
الوصف: Efficient 3-D mapping provides useful and detailed 3-D data for many applications. In this letter, we present a multisensor calibration and mapping method, to provide highly efficient and relatively accurate colored mapping for GPS-/global navigation satellite system-denied environments. The sensor data include 3-D laser scanning point clouds and camera images. A simultaneous localization and mapping (SLAM)-assisted calibration method is first proposed for multiple multibeam light detection and ranging (LiDAR) and multiple camera calibration. An improved SLAM method with loop closure is proposed for 3-D mapping. With the proposed calibration and mapping methods, centimeter-level colored point clouds can be obtained efficiently. The proposed method was tested with both backpacked and car-mounted systems on indoor and outdoor scenes. Experimental results show the effectiveness and efficiency of the proposed calibration and mapping methods.
تدمد: 1558-0571
1545-598X
DOI: 10.1109/lgrs.2019.2916844
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2fd7fc9d069217f4d0e4cb974401b95e
https://doi.org/10.1109/lgrs.2019.2916844
Rights: CLOSED
رقم الانضمام: edsair.doi...........2fd7fc9d069217f4d0e4cb974401b95e
قاعدة البيانات: OpenAIRE
الوصف
تدمد:15580571
1545598X
DOI:10.1109/lgrs.2019.2916844