TY - JOUR 
A1 - Morales Sánchez, Juan
AU - Verdú Monedero, Rafael
AU - Sancho Gómez, José Luis
AU - Weruaga Prieto, Luis
T1 - Multiple feature models for image matching
Y1 - 2005
UR - http://hdl.handle.net/10317/700
AB - The common approach to image matching is to detect spatial features present in both images and create a mapping that relates both images. The main draw back of this method takes place when more than one matching is likely. A first simplification to this ambiguity is to represent with apara-metric model the point locus where the matching is highly likely,and then use a POCS(projection on to convex sets)procedure combined with Tikhonov regularization that results in the  mapping vectors. However,if there is more than one model perpixel,the  regularization and constrainforcing process faces a multiplechoice dilemma that has no easy solution. This work proposes a frame work to overcome this draw  back: the combined projection over multiple models base don the norm of the projection–pointdis-tance. This approach is tested on a stereo-pair that presents multiple choices of similar likelihood.
KW - Teoría de la Señal y las Comunicaciones
KW - Modelo paramétrico
KW - POCS (Proyección de Conjuntos Convexos)
KW - Regularización de Tikhonov
KW - Mapa de vectores
LA - eng
PB - IEEE Institute of Electrical and Electronics
ER -