Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Vanishing Point Detection by Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Vanishing Point Detection without Any A Priori Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Metric Rectification for Perspective Images of Planes
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Physics-Based 3D Position Analysis of a Soccer Ball from Monocular Image Sequences
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Single view based measurement on space planes
Journal of Computer Science and Technology
Reconstruction of structured scenes from two uncalibrated images
Pattern Recognition Letters
Least-squares 3D reconstruction from one or more views and geometric clues
Computer Vision and Image Understanding
Single view based pose estimation from circle or parallel lines
Pattern Recognition Letters
What can we learn about the scene structure from three orthogonal vanishing points in images
Pattern Recognition Letters
Least-squares 3D reconstruction from one or more views and geometric clues
Computer Vision and Image Understanding
Distance measurement in panoramic video
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Pose estimation from circle or parallel lines in a single image
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Vision Based Position Control for MAVs Using One Single Circular Landmark
Journal of Intelligent and Robotic Systems
Improved feature extraction and matching in urban environments based on 3D viewpoint normalization
Computer Vision and Image Understanding
Three dimensional reconstruction of structured scenes based on vanishing points
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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The problem of how to retrieve Euclidean entities of a 3D scene from a single uncalibrated image is studied in this paper. We first present two methods to compute the camera projection matrix through the homography of a reference space plane and its vertical vanishing point. Then, we show how to use the projection matrix and some available scene constraints to retrieve geometrical entities of the scene, such as height of an object on the reference plane, measurements on a vertical or arbitrary plane with respect to the reference plane, distance from a point to a line, etc. In particular, the method is further employed to compute the volume and surface area of some regular and symmetric objects from a single image, the undertaking seems no similar report in the literature to our knowledge. In addition, all the algorithms are formulated in an explicit and linear geometric framework, and the involved computation is linear. Finally, extensive experiments on simulated data and real images as well as a comparative test with a closely related method in the literature validate our proposed methods.