ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
On Computing Metric Upgrades of Projective Reconstructions Under the Rectangular Pixel Assumption
SMILE '00 Revised Papers from Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments
Two-Frame Wide Baseline Matching
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
3D reconstruction based on SIFT and Harris feature points
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Live three-dimensional reconstruction system with stereo vision display
Computers and Electrical Engineering
| Hi-index | 0.00 |
In this paper, we describe a novel method to create the complete 3D model of the object on uncalibrated images. First, we match the points both detected by multi-scale Harris corner detection algorithm and line detection technique. Second, we perform a projected reconstruction based on factorization using Singular Value Decomposition (SVD). After that, we are able to upgrade from projective to Euclidean structure and then eliminate the ambiguity in Euclidean reconstruction. Finally, we use 3D registration algorithm based on common points to build the whole 3D model of the object. Sufficient experiments proved the validity and efficiency of the method.