Title :
Fundamental Matrix Estimation via TIP - Transfer of Invariant Parameters
Author :
Riggi, Frank ; Toews, Matthew ; Arbel, Tal
Author_Institution :
Centre for Intelligent Machines, McGill Univ., Montreal, Que.
Abstract :
The fundamental matrix (FM) represents the perspective transform between two or more uncalibrated images of a stationary scene, and is traditionally estimated based on 2-parameter point-to-point correspondences between image pairs. Recent invariant correspondence techniques however, provide robust correspondences in terms of 4 to 6-parameter invariant regions. Such correspondences contain important information regarding scene geometry, information which is lost in FM estimation techniques based solely on 2-parameter point translation. In this article, we present a method of incorporating this additional information into point-based FM estimation routines, entitled TIP (transfer of invariant parameters). The TIP method transforms invariant correspondence parameters into additional point correspondences, which can be used with FM estimation routines. Experimentation shows that the TIP methods result in more robust FM estimates in the case of sparse correspondence, and allows estimation based on as few as 3 correspondences in the case of affine-invariant features
Keywords :
image processing; sparse matrices; affine-invariant features; fundamental matrix estimation; image pairs; invariant correspondence techniques; sparse correspondence; transfer of invariant parameters; Cameras; Detectors; Image reconstruction; Information geometry; Layout; Lighting; Pattern recognition; Robustness; Sampling methods;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.588