Jianxin Shi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Jianxin Shi has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jingbo Zhou
School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication - Tiejun Li
School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication - Yuehua Li
School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication - Ziheng Zhang
School of Mechanical Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
1 shared publication
Latest Publications
- Open Access
Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System
Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.
Open AccessAdaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System
Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.