TY - GEN
T1 - Bifocal matching using multiple geometrical solutions
AU - Carrasco, Miguel
AU - Mery, Domingo
PY - 2011
Y1 - 2011
N2 - Determining point-to-point correspondence in multiple images is a complex problem because of the multiple geometric and photometric transformations and/or occlusions that the same point can undergo in corresponding images. This paper presents a method of point-to-point correspondence analysis based on the combination of two techniques: (1) correspondence analysis through similarity of invariant features, and (2) combination of multiple partial solutions through bifocal geometry. This method is quite novel because it allows the determination of point-to-point geometric correspondence by means of the intersection of multiple partial solutions that are weighted through the MLESAC algorithm. The main advantage of our method is the extension of the algorithms based on the correspondence of invariant descriptors, generalizing the problem of correspondence to a geometric model in multiple views. In the sequences used we got an F-score = 97% at a distance of less than 1 pixel. These results show the effectiveness of the method and potentially can be used in a wide range of applications.
AB - Determining point-to-point correspondence in multiple images is a complex problem because of the multiple geometric and photometric transformations and/or occlusions that the same point can undergo in corresponding images. This paper presents a method of point-to-point correspondence analysis based on the combination of two techniques: (1) correspondence analysis through similarity of invariant features, and (2) combination of multiple partial solutions through bifocal geometry. This method is quite novel because it allows the determination of point-to-point geometric correspondence by means of the intersection of multiple partial solutions that are weighted through the MLESAC algorithm. The main advantage of our method is the extension of the algorithms based on the correspondence of invariant descriptors, generalizing the problem of correspondence to a geometric model in multiple views. In the sequences used we got an F-score = 97% at a distance of less than 1 pixel. These results show the effectiveness of the method and potentially can be used in a wide range of applications.
KW - computer vision
KW - correspondence problem
KW - multiple view geometry
KW - tracking
UR - http://www.scopus.com/inward/record.url?scp=82155197259&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25346-1_18
DO - 10.1007/978-3-642-25346-1_18
M3 - Conference contribution
AN - SCOPUS:82155197259
SN - 9783642253454
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 192
EP - 203
BT - Advances in Image and Video Technology - 5th Pacific Rim Symposium, PSIVT 2011, Proceedings
T2 - 5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011
Y2 - 20 November 2011 through 23 November 2011
ER -