Research on precise modeling of buildings based on multi-source data fusion of air to ground

Li, Yongqiang; Niu, Lubiao; Yang, Shasha; Li, Lixue; Zhang, Xitong

doi:10.1117/12.2234689

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…It is necessary to set up multiple point clouds at multiple fixed sites with different fields of view when TLS collects the point cloud of a structure. The obtained point clouds need to be spatially matched to reflect the 3D information of the structure [28][29][30]. Especially in the face of the goal of complex structure, TLS must ensure the integrity of point cloud acquisition by increasing the number of stations.…”

Section: Tls Point Cloud Facade Hole Repairmentioning

confidence: 99%

Feature Analysis of Scanning Point Cloud of Structure and Research on Hole Repair Technology Considering Space-Ground Multi-Source 3D Data Acquisition

Gan

Yuan

et al. 2022

Sensors

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As one of the best means of obtaining the geometry information of special shaped structures, point cloud data acquisition can be achieved by laser scanning or photogrammetry. However, there are some differences in the quantity, quality, and information type of point clouds obtained by different methods when collecting point clouds of the same structure, due to differences in sensor mechanisms and collection paths. Thus, this study aimed to combine the complementary advantages of multi-source point cloud data and provide the high-quality basic data required for structure measurement and modeling. Specifically, low-altitude photogrammetry technologies such as hand-held laser scanners (HLS), terrestrial laser scanners (TLS), and unmanned aerial systems (UAS) were adopted to collect point cloud data of the same special-shaped structure in different paths. The advantages and disadvantages of different point cloud acquisition methods of special-shaped structures were analyzed from the perspective of the point cloud acquisition mechanism of different sensors, point cloud data integrity, and single-point geometric characteristics of the point cloud. Additionally, a point cloud void repair technology based on the TLS point cloud was proposed according to the analysis results. Under the premise of unifying the spatial position relationship of the three point clouds, the M3C2 distance algorithm was performed to extract the point clouds with significant spatial position differences in the same area of the structure from the three point clouds. Meanwhile, the single-point geometric feature differences of the multi-source point cloud in the area with the same neighborhood radius was calculated. With the kernel density distribution of the feature difference, the feature points filtered from the HLS point cloud and the TLS point cloud were fused to enrich the number of feature points in the TLS point cloud. In addition, the TLS point cloud voids were located by raster projection, and the point clouds within the void range were extracted, or the closest points were retrieved from the other two heterologous point clouds, to repair the top surface and façade voids of the TLS point cloud. Finally, high-quality basic point cloud data of the special-shaped structure were generated.

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Section: Tls Point Cloud Facade Hole Repairmentioning

confidence: 99%

Feature Analysis of Scanning Point Cloud of Structure and Research on Hole Repair Technology Considering Space-Ground Multi-Source 3D Data Acquisition

Gan

Yuan

et al. 2022

Sensors

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“…Medical imaging cloud products will realize device hierarchical data interconnection, device hierarchical data information sharing, device hierarchical data storage, and improve the level of device hierarchical data diagnosis in primary hospitals. The in-house PACS storage is directly connected to the cloud, and the cloud performs storage, retrieval, archiving, and advanced functions such as mobilization and 3D [40]. Collaborate across medical units to achieve device hierarchical data sharing within the region, providing remote reading, remote reporting, and device hierarchical data big data analysis.…”

Section: Intelligent Telemedicine System Applicationmentioning

confidence: 99%

Research on Hierarchical Data Fusion of Intelligent Medical Monitoring

Xue

Lu²,

Wang³

et al. 2020

IEEE Access

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The IOT-based intelligent telemedicine system is an important direction for future development. It combines information space and physical space to inform and network people's living environment. The distribution of medical resources in China is extremely uneven. There are many excellent medical resources in big cities. The resources of small and medium-sized cities are very few, which leads to patients going to large city hospitals for medical treatment, resulting in hospital overcrowding. Intelligent telemedicine system sinks excellent medical resources. Patients can also enjoy the excellent medical resources of the big city hospitals in the local area. Therefore, the use of advanced networks and science and technology, the integration of information technology and medical technology, the establishment of intelligent telemedicine system, will certainly optimize the hospital business process. This paper proposes research on multi-level data fusion under intelligent medical monitoring, which will improve its resource utilization and work efficiency, and promote hospital hierarchical data construction. Innovative use of Internet of Things technology promotes academic exchanges among hospitals, which improves doctors' technical skills, and hospital medical standards. The development of the Internet of Things is significant to the development of China's medical industry. It is hoped that this article can help the development of telemedicine in China.

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“…By clicking on the personal ID number, you can enter the personal physician analysis page, and all the diagnostic records will be arranged according to the disease name, combined with the misdiagnosis rate. When the doctor understands that the probability of personal misdiagnosis is too high, the patient can comprehensively summarize and analyze the cause of the misdiagnosis [35], [36]. In addition, the system will automatically enter the database in the background, as a misdiagnosis analysis of the alternate data information.…”

Section: A Function Testmentioning

confidence: 99%

Research on Data Mining Application of Orthopedic Rehabilitation Information for Smart Medical

Zhang

2019

IEEE Access

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Due to the small scale, low technical level, and limited scope of application of artificial intelligence in the field of traditional Chinese medicine orthopedics, there are many problems in the development of this area. Driven by precise and minimally invasive medical concepts, the integration of artificial intelligence and data mining technologies (such as the Internet, cloud computing, and big data) will further profoundly change the face of smart healthcare in the future, which will bring great challenges to traditional Chinese medicine orthopedics, and Change opportunities for your own development. In order for artificial intelligence to provide good diagnosis and treatment services for a large number of patients with orthopaedic diseases, progress still needs to be made with the technology and joint efforts of many orthopaedic experts and scholars. This article uses data mining techniques to optimize orthopedic rehabilitation information. Test results show that the system is faster and more convenient. Artificial intelligence technology will be used for intelligent medical treatment of orthopedic diseases in the future. It will become an essential assistant for clinicians and make a significant contribution to the diagnosis of various orthopedic diseases.

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Research on precise modeling of buildings based on multi-source data fusion of air to ground

Cited by 4 publications

References 1 publication

Feature Analysis of Scanning Point Cloud of Structure and Research on Hole Repair Technology Considering Space-Ground Multi-Source 3D Data Acquisition

Feature Analysis of Scanning Point Cloud of Structure and Research on Hole Repair Technology Considering Space-Ground Multi-Source 3D Data Acquisition

Research on Hierarchical Data Fusion of Intelligent Medical Monitoring

Research on Data Mining Application of Orthopedic Rehabilitation Information for Smart Medical

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