IEEE Transactions on Pattern Analysis and Machine Intelligence
Using vanishing points for camera calibration
International Journal of Computer Vision
Surface Parametrization and Curvature Measurement of Arbitrary 3-D Objects: Five Practical Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
A theory of self-calibration of a moving camera
International Journal of Computer Vision
Curvature approximation for triangulated surfaces
Geometric modelling
Computer Vision and Image Understanding
On surface normal and Gaussian curvature approximations given data sampled from a smooth surface
Computer Aided Geometric Design
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Self-Calibration from Image Triplets
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Estimating the tensor of curvature of a surface from a polyhedral approximation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Camera Calibration from Images of Spheres
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Accurate optical flow computation under non-uniform brightness variations
Computer Vision and Image Understanding
DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simple camera calibration from a single image using five points on two orthogonal 1-D objects
IEEE Transactions on Image Processing
Critical nets and beta-stable features for image matching
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
SIFT Flow: Dense Correspondence across Scenes and Its Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Calibration Using Symmetric Objects
IEEE Transactions on Image Processing
A Stratified Approach for Camera Calibration Using Spheres
IEEE Transactions on Image Processing
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Recovering three-dimensional (3D) points from image correspondences is an important and fundamental task in computer vision. Traditionally, the task is completed by triangulation whose accuracy has its limitation in some applications. In this paper, we present a framework that incorporates surface characteristics such as Gaussian and mean curvatures into 3D point reconstruction to enhance the reconstruction accuracy. A Gaussian and mean curvature estimation scheme suitable to the proposed framework is also introduced in this paper. Based on this estimation scheme and the proposed framework, the 3D point recovery from image correspondences is formulated as an optimization problem with the surface curvatures modeled as soft constraints. To analyze the performance of proposed 3D reconstruction approach, we generated some synthetic data, including the points on the surfaces of a plane, a cylinder and a sphere, to test the approach. The experimental results demonstrated that the proposed framework can indeed improve the accuracy of 3D point reconstruction. Some real-image data were also tested and the results also confirm this point.