Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Canonic representations for the geometries of multiple projective views
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
A common framework for kinetic depth, reconstruction and motion for deformable objects
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Relative Affine Structure: Canonical Model for 3D From 2D Geometry and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Generalised Epipolar Constraints
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
A canonical framework for sequences of images
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
Reconstruction from image sequences by means of relative depths
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
On the geometry and algebra of the point and line correspondences between N images
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Motion analysis with a camera with unknown, and possibly varying intrinsic parameters
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Matching constraints and the joint image
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Recursive structure and motion estimation based on hybrid matching constraints
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Recursive structure from motion using hybrid matching constraints with error feedback
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
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Corresponding image points of a rigid object in a discrete sequence of images fulfil the so-called multilinear constraint.In this paper the continuous time analogue of thisconstraint, for a continuous stream of images, is introduced and studied.The constraint links the Taylor series expansion of the motion of the image points with theTaylor series expansion of the relative motion and orientation betweenthe object and the camera.The analysis is done both for calibrated and uncalibrated cameras.Two simplifications are also presented for the uncalibrated cameracase. One simplification is made using an affine reduction andthe so-called kinetic depths.The second simplification is based upon a projectivereduction with respect to the image of a planar configuration.The analysis shows that the constraint involving second-order derivativesare needed to determine camera motion. Experimentswith real and simulated data are also presented.