Name
Abstract | ||
|---|---|---|
This paper proposes a dynamic 3D reconstruction method for recovering a surface shape from a set of images that are captured by a hand-held camera. A light source is attached to the camera as a photometric constraint. Thus, we can effectively calculate photometric stereo using the relative moving camera. The key contributions of our work are a robust pixel matching method to build effective correspondences between images for normal estimation, and an optimization method to correct the deviation in the recovered surface shape that is caused by the non-ideal illumination in a close-range lighting condition. Specially we correct the recovered shape by adding an interpolation surface that is estimated using sparse control points from the structure from motion. The effectiveness of our method is verified on real datasets with a digital camera and a smart phone. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IECON.2018.8592826 | IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | Field | DocType |
3D reconstruction, photometric stereo, shape from motion and shading | Structure from motion,Iterative reconstruction,Surface reconstruction,Computer vision,Control theory,Interpolation,Digital camera,Artificial intelligence,Pixel,Engineering,Photometric stereo,3D reconstruction | Conference |
ISSN | Citations | PageRank |
1553-572X | 1 | 0.34 |
References | Authors | |
0 | 5 | |