Papers by Keyword: 3D Model Reconstruction

Abstract: Close-range photogrammetry is a technique of calculating the location, size and shape of measured object by photography whose object distance is generally not greater than 300 meters. Three-dimensional (3D) model reconstruction based on close-range photogrammetry has higher efficiency than that based on Light Detection And Ranging (LiDAR) technique since acquiring texture data simultaneously. This technology reduces the consuming time of 3D model reconstruction, while ensuring high precision. In this paper, processes and key technologies of 3D model reconstruction based on portable close-range photogrammetry are provided, and it feasibility of the technology is verified via taking Taizhou TV Tower as an example.

Abstract: The digital measurements of the back cover of a telephone receiver were carried out by a three dimensional measuring machine and the data point clouds of the contours were got. Using reverse engineering software, Imageware, the data point clouds were processed, including of data smoothing, data reducing, data point clouds resample, feature lines extracting and curve fitting. Based on the shape features of the research object, the 3D model of the back cover of the telephone receiver were reconstructed with the boundary curves and the scanning data point groups successfully. Precision evaluation was carried out to the 3D model and the error controlled within 0.2mm.

Abstract: This paper made the 3D model reconstruction of the V2500 turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, smoothed and filtered the point cloud data, took the rational simplification, finished pre-processing the point cloud data. Finally, the grayscale of space-image algorithm was used for fitting the edge of turban blade, and reconstructed the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.

Abstract: This paper made the 3D model reconstruction of the J34 turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, smoothed and filtered the point cloud data, took the rational simplification, finished pre-processing the point cloud data. Finally, the Laplacian of Guassian Detection was used for fitting the edge of turban blade, and reconstructed the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.

Abstract: This paper made the 3D model reconstruction of the CFM56-5B turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, smoothed and filtered the point cloud data, took the rational simplification, finished pre-processing the point cloud data. Finally, multi-scale genetic algorithm was used for fitting the edge of turban blade, and reconstructed the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.