Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Factorization Methods for Projective Structure and Motion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Paraperspective Factorization Method for Shape and Motion Recovery
A Paraperspective Factorization Method for Shape and Motion Recovery
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This study proposes a new factorization method for shape and motion recovery. In past, the fourth greatest singular value of the measurement matrix was ignored. But when noise is larger enough so that the fourth greatest singular value can not be ignored, it would be difficult to get reliable results by using the traditional factorization method. In order to acquire reliable results, We start with adopting an orthogonalization method to find a matrix which is composed of three mutually orthogonal vectors. By using this matrix another matrix can be obtained. Then, the two expected matrices which represent shape of object and motion of camera/object, can be obtained through normalization. This study also conducts several experiments to discuss the feasibility of the proposed method.