IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from motion using line correspondences
International Journal of Computer Vision
Subspace methods for recovering rigid motion I: algorithm and implementation
International Journal of Computer Vision
A theory of self-calibration of a moving camera
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Performance of optical flow techniques
International Journal of Computer Vision
Recursive non-linear estimation of discontinuous flow fields
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Self-calibration from multiple views with a rotating camera
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Optical flow estimation and the interaction between measurement errors at adjacent pixel positions
International Journal of Computer Vision
The first order expansion of motion equations in the uncalibrated case
Computer Vision and Image Understanding
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Effects of errors in the viewing geometry on shape estimation
Computer Vision and Image Understanding
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Hierarchical Model-Based Motion Estimation
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
Discrete-Time Rigidity-Constrained Optical Flow
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
Simultaneous Estimation of Viewing Geometry and Structure
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
The Modulus Constraint: A New Constraint for Self-Calibration
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Bias-Corrected Optical Flow Estimation for Road Vehicle Tracking
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Self-Calibration from Image Derivatives
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Instantaneous 3D motion from image derivatives using the Least Trimmed Square regression
Pattern Recognition Letters
3D motion from image derivatives using the least trimmed square regression
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
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This study investigates the problem of estimating camera calibration parameters from image motion fields induced by a rigidly moving camera with unknown parameters, where the image formation is modeled with a linear pinhole-camera model. The equations obtained show the flow to be separated into a component due to the translation and the calibration parameters and a component due to the rotation and the calibration parameters. A set of parameters encoding the latter component is linearly related to the flow, and from these parameters the calibration can be determined.However, as for discrete motion, in general it is not possible to decouple image measurements obtained from only two frames into translational and rotational components. Geometrically, the ambiguity takes the form of a part of the rotational component being parallel to the translational component, and thus the scene can be reconstructed only up to a projective transformation. In general, for full calibration at least four successive image frames are necessary, with the 3D rotation changing between the measurements.The geometric analysis gives rise to a direct self-calibration method that avoids computation of optical flow or point correspondences and uses only normal flow measurements. New constraints on the smoothness of the surfaces in view are formulated to relate structure and motion directly to image derivatives, and on the basis of these constraints the transformation of the viewing geometry between consecutive images is estimated. The calibration parameters are then estimated from the rotational components of several flow fields. As the proposed technique neither requires a special set up nor needs exact correspondence it is potentially useful for the calibration of active vision systems which have to acquire knowledge about their intrinsic parameters while they perform other tasks, or as a tool for analyzing image sequences in large video databases.