A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Regularization theory and neural networks architectures
Neural Computation
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Shape Recovery from Occluding Contours Using a Linear Smoother
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
The Softassign Procrustes Matching Algorithm
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Computing Structure and Motion of General 3D Curves from Monocular Sequences of Perspective Images
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
On the geometry and algebra of the point and line correspondences between N images
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Robust Visual Tracking for Non-Instrumented Augmented Reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
International Journal of Computer Vision
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Combining Edge and Texture Information for Real-Time Accurate 3D Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Contour Point Tracking by Enforcement of Rigidity Constraints
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Real Time Localization and 3D Reconstruction
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Correspondence-Free Determination of the Affine Fundamental Matrix
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correspondence-free Structure from Motion
International Journal of Computer Vision
Structure-oriented contour representation and matching for engineering shapes
Computer-Aided Design
Practical Global Optimization for Multiview Geometry
International Journal of Computer Vision
Balanced Exploration and Exploitation Model Search for Efficient Epipolar Geometry Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow
Proceedings of the 30th DAGM symposium on Pattern Recognition
SIFT Flow: Dense Correspondence across Different Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Robust Optimal Pose Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Pose Priors for Simultaneously Solving Alignment and Correspondence
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Feature Correspondence Via Graph Matching: Models and Global Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Deformable Surface Augmentation in Spite of Self-Occlusions
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Structure-from-motion using lines: Representation, triangulation, and bundle adjustment
Computer Vision and Image Understanding
Contour/texture approach for visual tracking
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Simultaneous in-plane motion estimation and point matching using geometric cues only
WMVC'09 Proceedings of the 2009 international conference on Motion and video computing
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Probabilistic subgraph matching based on convex relaxation
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
International Journal of Computer Vision
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Traditionally, the camera pose recovery problem has been formulated as one of estimating the optimal camera pose given a set of point correspondences. This critically depends on the accuracy of the point correspondences and would have problems in dealing with ambiguous features such as edge contours and high visual clutter. Joint estimation of camera pose and correspondence attempts to improve performance by explicitly acknowledging the chicken and egg nature of the pose and correspondence problem. However, such joint approaches for the two-view problem are still few and even then, they face problems when scenes contain largely edge cues with few corners, due to the fact that epipolar geometry only provides a "soft" point to line constraint. Viewed from the perspective of point set registration, the point matching process can be regarded as the registration of points while preserving their relative positions (i.e. preserving scene coherence). By demanding that the point set should be transformed coherently across views, this framework leverages on higher level perceptual information such as the shape of the contour. While thus potentially allowing registration of non-unique edge points, the registration framework in its traditional form is subject to substantial point localization error and is thus not suitable for estimating camera pose. In this paper, we introduce an algorithm which jointly estimates camera pose and correspondence within a point set registration framework based on motion coherence, with the camera pose helping to localize the edge registration, while the "ambiguous" edge information helps to guide camera pose computation. The algorithm can compute camera pose over large displacements and by utilizing the non-unique edge points can recover camera pose from what were previously regarded as feature-impoverished SfM scenes. Our algorithm is also sufficiently flexible to incorporate high dimensional feature descriptors and works well on traditional SfM scenes with adequate numbers of unique corners.