Object Model Reconstruction

Abstract

3D model reconstruction is essential to 3D printing, reverse engineering, prototyping, orthotics and prosthetics. Nowadays, along with the rapid growth in 3D printer, how to scan a real-world object efficiently becomes more important. We developed an automated object model reconstruction system, which produced a delicate mesh model with high-resolution texture.

In the proposed system, we used structured light device as our scanning equipment. Our work contains three main parts. The first part is camera calibration and coordinate alignment. The second part is data acquisition and point cloud alignment. The final part is model reconstruction and texture mapping. In the procedure of calibration, Zhang's method was used to calibrate our camera. The chessboard approach helped us with finding the coordinate system alignment between multiple views. Next, we used background subtraction and radius outlier removal method to obtain a group of foreground point cloud. We then transformed all point clouds from the camera coordinate system to the world coordinate system by calibration results. With a group of noise-free clouds, we used the color-supported ICP algorithm to get an accurate alignment result. We further refined the relation between camera poses by a global optimization method. The final part was the reconstruction of mesh model and texture mapping. We applied Poisson mesh reconstruction technique, constructed a mesh model from the point cloud. With the camera intrinsic and extrinsic parameters, we simulated the camera model, and back projected high-resolution photos on the model in the end.

According to our experimental results, the proposed system can achieve efficient object scan. The whole scanning and reconstruction process can be completed in about 2 minutes, including 106 seconds of the scanning time and 22 seconds of the computing time. On the other hand, with the camera calibration, alignment algorithm improvement and optimization, our approach can accurately reconstruct the 3D object model. The model size is about 4.25% of the real object size. Besides, our system provided an automated operating interface. It is able to complete an entire scanning procedure in one-click.

Results