Meizhen Wang
Biographic Data
| ID | 9844326 |
|---|---|
| NAME | Meizhen Wang |
| GIVEN NAMES | Meizhen |
| FAMILY NAME | Wang |
| SIGNATURE | WANG M |
| AFFILIATIONS | Nanjing Normal University |
| ORCID | 0000-0002-4135-5073 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
A Spatial Information Extraction Method Based on Multi-Modal Social Media Data
With the proliferation and development of social media platforms, social media data have become an important source for acquiring spatiotemporal information on various urban events. Providing accurate spatiotemporal information for events contributes to enhancing the capabilities of urban management and emergency responses. However, existing research regarding mining spatiotemporal information of events often solely focuses on textual content and…
D Change Detection Using Adaptive Thresholds Based on Local Point Cloud Density
In recent years, because of highly developed LiDAR (Light Detection and Ranging) technologies, there has been increasing demand for 3D change detection in urban monitoring, urban model updating, and disaster assessment. In order to improve the effectiveness of 3D change detection based on point clouds, an approach for 3D change detection using point-based comparison is presented in this paper. To avoid density variation in point clouds, adaptive …
A Cost Function for the Uncertainty of Matching Point Distribution on Image Registration
Computing the homography matrix using the known matching points is a key step in computer vision for image registration. In practice, the number, accuracy, and distribution of the known matching points can affect the uncertainty of the homography matrix. This study mainly focuses on the effect of matching point distribution on image registration. First, horizontal dilution of precision (HDOP) is derived to measure the influence of the distributio…
Quantification Method for the Uncertainty of Matching Point Distribution on 3D Reconstruction
Matching points are the direct data sources of the fundamental matrix, camera parameters, and point cloud calculation. Thus, their uncertainty has a direct influence on the quality of image-based 3D reconstruction and is dependent on the number, accuracy, and distribution of the matching points. This study mainly focuses on the uncertainty of matching point distribution. First, horizontal dilution of precision (HDOP) is used to quantify the featu…
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Quantification Method for the Uncertainty of Matching Point Distribution on 3D Reconstruction
Matching points are the direct data sources of the fundamental matrix, camera parameters, and point cloud calculation. Thus, their uncertainty has a direct influence on the quality of image-based 3D reconstruction and is dependent on the number, accuracy, and distribution of the matching points. This study mainly focuses on the uncertainty of matching point distribution. First, horizontal dilution of precision (HDOP) is used to quantify the featu…
D Change Detection Using Adaptive Thresholds Based on Local Point Cloud Density
In recent years, because of highly developed LiDAR (Light Detection and Ranging) technologies, there has been increasing demand for 3D change detection in urban monitoring, urban model updating, and disaster assessment. In order to improve the effectiveness of 3D change detection based on point clouds, an approach for 3D change detection using point-based comparison is presented in this paper. To avoid density variation in point clouds, adaptive …
A Cost Function for the Uncertainty of Matching Point Distribution on Image Registration
Computing the homography matrix using the known matching points is a key step in computer vision for image registration. In practice, the number, accuracy, and distribution of the known matching points can affect the uncertainty of the homography matrix. This study mainly focuses on the effect of matching point distribution on image registration. First, horizontal dilution of precision (HDOP) is derived to measure the influence of the distributio…
A Spatial Information Extraction Method Based on Multi-Modal Social Media Data
With the proliferation and development of social media platforms, social media data have become an important source for acquiring spatiotemporal information on various urban events. Providing accurate spatiotemporal information for events contributes to enhancing the capabilities of urban management and emergency responses. However, existing research regarding mining spatiotemporal information of events often solely focuses on textual content and…
Computer Science (4 works) · Artificial Intelligence (3 works) · Mathematics (3 works) · Computer vision (2 works) · Geography (2 works) · Geometry (2 works) · Point cloud (2 works) · Point set registration (2 works) · Remote sensing (2 works) · Remote Sensing and LiDAR Applications (2 works)