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Found 6 papers, 0 papers with code
Single-image driven 3d viewpoint training data augmentation for effective wine label recognition
Confronting the critical challenge of insufficient training data in the field of complex image recognition, this paper introduces a novel 3D viewpoint augmentation technique specifically tailored for wine label recognition.
Equivalence of Two Expressions of Principal Line
Geometry-based camera calibration using principal line is more precise and robust than calibration using optimization approaches; therefore, several researches try to re-derive the principal line from different views of 2D projective geometry to increase alternatives of the calibration process.
Visualizing and Alleviating the Effect of Radial Distortion on Camera Calibration Using Principal Lines
Preparing appropriate images for camera calibration is crucial to obtain accurate results.
A New Technique of Camera Calibration: A Geometric Approach Based on Principal Lines
Camera calibration is a crucial prerequisite in many applications of computer vision.
Descriptor Ensemble: An Unsupervised Approach to Descriptor Fusion in the Homography Space
Inspired by the observation that the homographies of correct feature correspondences vary smoothly along the spatial domain, our approach stands on the unsupervised nature of feature matching, and can select a good descriptor for matching each feature point.
Robust Feature Matching with Alternate Hough and Inverted Hough Transforms
Inspired by the fact that nearby features on the same object share coherent homographies in matching, we cast the task of feature matching as a density estimation problem in the Hough space spanned by the hypotheses of homographies.
