Trinocular Stereo Vision for Robotics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Theory and Practice of Projective Rectification
International Journal of Computer Vision
A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
On Robust Rectification for Uncalibrated Images
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Applications of a direct algorithm for the rectification of uncalibrated images
Information Sciences—Informatics and Computer Science: An International Journal
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Projective Rectification with Reduced Geometric Distortion for Stereo Vision and Stereoscopic Video
Journal of Intelligent and Robotic Systems
Stereo vision using two PTZ cameras
Computer Vision and Image Understanding
Multiresolution and wide-scope depth estimation using a dual-PTZ-camera system
IEEE Transactions on Image Processing
Epipolar line estimation and rectification for stereo image pairs
IEEE Transactions on Image Processing
Estimation of F-Matrix and image rectification by double quaternion
Information Sciences: an International Journal
A new method of stereo localization using Dual-PTZ-Cameras
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
Closed-form stereo image rectification
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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In this paper, an algorithm for rectifying heterogeneous and uncalibrated pairs of stereo images is presented. In particular, a pair of images is captured by using a combination of static and dynamic cameras at unequal zoom, thus having different focal lengths and/or image resolutions. The rectification of such pairs of images is made in two steps. In the first step, image shrinking based on focal ratios is performed for compensating the effect of unequal zoom levels followed by a zero padding on the smaller image for making the images of equal size. In the second step, rectification transformations are calculated by solving a nonlinear constrained optimization problem for a given set of pairs of corresponding points (SIFT descriptors) between stereo images. Experiments are performed to evaluate the performance of the proposed method and assess the improvements of the proposed method over direct rectification.