Invariant Descriptors for 3D Object Recognition and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Geometric invariance in computer vision
Geometric invariance in computer vision
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)
Motion from point matches using affine epipolar geometry
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Navigation using affine structure from motion
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Artificial Intelligence - Special volume on computer vision
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
Projective Structure from Uncalibrated Images: Structure From Motion and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
On the Optimization Criteria Used in Two-View Motion Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Epipolar geometry of catadioptric stereo systems with planar mirrors
Image and Vision Computing
The quasi-perspective model: Geometric properties and 3D reconstruction
Pattern Recognition
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This paper addresses the recovery of structure and motion from two uncalibrated images of a scene under full perspective or under affine projection. Epipolar geometry, projective reconstruction, and affine reconstruction are elaborated in a way such that everyone having knowledge of linear algebra can understand the discussion without difficulty. A general expression of the fundamental matrix is derived which is valid for any projection model without lens distortion (including full perspective and affine camera). A new technique for affine reconstruction from two affine images is developed, which consists in first estimating the affine epipolar geometry and then performing a triangulation for each point match with respect to an implicit common affine basis. This technique is very efficient.