Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Geometric computation for machine vision
Geometric computation for machine vision
3D motion recovery via affine epipolar geometry
International Journal of Computer Vision
International Journal of Computer Vision
Object recognition by combining paraperspective images
International Journal of Computer Vision
Self-calibration of an affine camera from multiple views
International Journal of Computer Vision
A Paraperspective Factorization Method for Shape and Motion Recovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Group Theoretical Methods in Image Understanding
Group Theoretical Methods in Image Understanding
Evaluation and Selection of Models for Motion Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Structure from motion and photometric stereo for dense 3D shape recovery
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
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In order to reconstruct 3-D Euclidean shape by the Tomasi-Kanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and paraperspective. We present a new method that does not require any such specific models. We show that a minimal requirement for an affine camera to mimic perspective projection leads to a unique camera model, called symmetric affine camera, which has two free functions. We determine their values from input images by linear computation and demonstrate by experiments that an appropriate camera model is automatically selected.