Representing stereo data with the Delaunay triangulation
Artificial Intelligence
Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
A General Surface Approach to the Integration of a Set of Range Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Creating full view panoramic image mosaics and environment maps
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Applying Two-dimensional Delaunay Triangulation to Stereo Data Interpolation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
3D Model Acquisition from Extended Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Automatic reconstruction of 3D objects using a mobile monoscopic camera
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
A unifying framework for structure and motion recovery from image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Modeling and Rendering Architecture from Photographs:
Modeling and Rendering Architecture from Photographs:
Maintaining Multiple Motion Model Hypotheses Over Many Views to Recover Matching and Structure
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Surface Reconstruction from Feature Based Stereo
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Video Mosaics for Virtual Environments
IEEE Computer Graphics and Applications
Visual Navigation for Mobile Robots: A Survey
Journal of Intelligent and Robotic Systems
High resolution surface reconstruction from overlapping multiple-views
Proceedings of the twenty-fifth annual symposium on Computational geometry
Photo-consistent planar patches from unstructured cloud of points
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Light field modeling and its application to remote sensing image simulation
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
3D Scene Reconstruction from Multiple Spherical Stereo Pairs
International Journal of Computer Vision
Manifold surface reconstruction of an environment from sparse Structure-from-Motion data
Computer Vision and Image Understanding
Editor's Choice Article: Image-consistent patches from unstructured points with J-linkage
Image and Vision Computing
Incremental 3D reconstruction using Bayesian learning
Applied Intelligence
| Hi-index | 0.00 |
Sparse 3D measurements of real scenes are readily estimated from N-view image sequences using structure-from-motion techniques. In this paper, we present a geometric theory for reconstruction of surface models from sparse 3D data captured from N camera views. Based on this theory, we introduce a general N-view algorithm for reconstruction of 3D models of arbitrary scenes from sparse data. This algorithm reconstructs a surface model which converges to an approximation of the real scene surfaces and is consistent with the feature visibility in all N-views. To achieve efficient reconstruction independent of the number of views a recursive reconstruction algorithm is developed which integrates the feature visibility independently for each view. This approach is shown to converge to an approximation of the real scene structure and have a computational cost which is linear in the number of views. It is assumed that structure-from-motion estimates of 3D feature locations are consistent with the multiple view visual geometry and do not contain outliers. Uncertainty in 3D feature estimates is incorporated in the feature visibility to achieve reliable reconstruction in the presence of noise inherent in estimates of 3D scene structure from real image sequences. Results are presented for reconstruction of both real and synthetic scenes together with an evaluation of the reconstruction performance in the presence of noise. The algorithm presented in this paper provides a reliable and computationally efficient approach to model reconstruction from sparse 3D scene data.