Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Fast normalized cross correlation for defect detection
Pattern Recognition Letters
A Quasi-Dense Approach to Surface Reconstruction from Uncalibrated Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
3D S.O.M.: a commercial software solution to 3D scanning
Graphical Models - Special issue: Vision and computer graphics
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Poisson surface reconstruction
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Detailed Real-Time Urban 3D Reconstruction from Video
International Journal of Computer Vision
Post-processing of scanned 3D surface data
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
Hi-index | 0.00 |
In this paper, we present an automatic and efficient image based modeling system which can create objects' 3D models directly from images captured from different viewpoints. The system firstly uses structure from motion to generate camera parameters and sparse 3D patches. Then, a conservative plane based sweep stereo method on GPU is used to compute quasi-dense depth maps which usually have many holes and create many new patches. Finally, a simplified patch based surface growing method is used to compute dense depth maps together with a dense 3D geometry shape model. Different from others, our system constructs patches from reconstructed points by structure from motion. These patches grow denser gradually from sparse, quasi dense to dense through the following expansion steps. During expansion, conservative strategies are used and object normal is not optimized but gradually computed from reconstructed quasi dense neighbors. This makes the system work better and faster on more difficult scenarios, e.g. wide baseline, varying illumination. Experiments show that our method can generate high fidelity 3D object shape models quite efficiently.