PE&RS January 2018 Full - page 32

References
Alcantarilla, P.F., J. Nuevo, and A. Bartoli, 2013. Fast explicit
diffusion for accelerated features in nonlinear scale spaces,
Proceedings of the British Machine Vision Conference
.
Ambai, M., and Y. Yoshida, 2011. CARD: compact and real-time
descriptors,
Proceedings of the IEEE International Conference on
Computer Vision
, 2011, pp. 97–104.
Bay, H., T. Tuytelaars, and L. Van Gool, 2006. SURF: Speeded up
robust features,
Proceedings of the European Conference on
Computer Vision
.
Chien, H.J., C.C. Chuang, C.Y. Chen, and R. Klette, 2016. When to
use what feature? SIFT, SURF, ORB, or A-KAZE features for
monocular visual odometry,
Image and Vision Computing - New
Zealand (IVCNZ)
, pp. 2151–2205.
Cruz-Mota, J., I. Bogdanova, B. Paquier, M. Bierlaire, and J.P. Thiran,
2012. Scale invariant feature transform on the sphere: Theory
and applications,
International Journal of Computer Vision
,
98(2):217–241.
Fangi, G., and C. Nardinocchi, 2013. Photogrammetric processing
of spherical panoramas,
The Photogrammetric Record
,
28(143):293–311.
Hamid, N., A. Yahya, B.R. Ahmad, and O.M. Al-qershi, 2012. A
comparison between using SIFT and SURF for characteristic
region based image steganography,
International Journal of
Computer Science Issues (IJCSI)
, 9(3).
Ishiguro, H., K.C. Ng, R. Capella, and M.M. Trivedi, 2003.
Omnidirectional image-based modeling: Three approaches to
approximated plenoptic representations,
Machine Vision and
Applications
, 14(2):94–102.
Panchal, P.M., S.R. Panchal, and S.K. Shah, 2013. A comparison of
SIFT and SURF,
International Journal of Innovative Research in
Computer and Communication Engineering
, 1(2):323-327.
Johansen, S., and B. Nielsen, 2014, Outlier detection algorithms
for least squares time series regression, URL:
org/10.2139/ssrn.2510281
(last date accessed: 05 December 2017).
Juan, L., and Q. Gwun, 2009. A comparison of SIFT, PCA-SIFT and
SURF,
International Journal of Image Processing (IJIP)
, 3(4):143–152.
Klette, R., 2014.
Concise Computer Vision
. Springer, London.
Koch, K.R., 1999. Parameter eEstimation and Hypothesis Testing in
Linear Models, Second Edition, Springer, Berlin.
Leutenegger, S., M.Chli, and R.Y. Siegwart, 2011. BRISK: Binary
robust invariant scalable keypoints,
Proceedings of the IEEE
International Conference on Computer Vision
, pp. 2548–2555.
Longuet-Higgins, H.C., 1981. A computer algorithm for reconstructing
a scene from two projections,
Nature
, 293(5828):133–135.
Lowe, D.G., 1999. Object recognition from local scale-invariant
features,
Proceedings of the International Conference on
Computer Vision.
, 2:1150-1157.
Lowe, D.G., 2004. Distinctive image features from scale-invariant
keypoints,
International Journal of Computer Vision
, 60(2):91–110.
Mauthner, T., F. Fraundorfer, and H. Bischof, 2006. Region matching
for omnidirectional images using virtual camera planes,
Proceedings of the Computer Vision Winter Workshop
, pp. 93–98.
Mikolajczyk, K., T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F.
Schaffalitzky, T. Kadir, and L. Van Gool, 2005. A comparison of
affine region detectors,
International Journal of Computer Vision
,
65(1):43–72.
Nayar, S.K., 1997. Catadioptric omnidirectional camera,
Proceedings
of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition
, pp. 482.
Raguram, R., O. Chum, M. Pollefeys, J. Matas, and J. Frahm,
2013. USAC: A universal framework for random sample
consensus.,
IEEE Transactions on Pattern Analysis and Machine
Intelligence
, 35(8):2022–2038.
Rangelova, E., G. Fotopoulos, and M.G. Sideris, 2009. On the use
of iterative re-weighting least-squares and outlier detection for
empirically modelling rates of vertical displacement,
Journal of
Geodesy
, 83(6):523–535.
Rublee, E., V. Rabaud, K. Konolige, and G. Bradski, 2011. ORB:
An efficient alternative to SIFT or SURF,
Proceedings of the
International Conference on Computer Vision
, pp. 2564–2571.
Svoboda, T., and T. Pajdla, 2001. Matching in catadioptric images
with appropriate windows and outliers removal,
Proceedings of
the 9
th
International Conference on Computer Analysis of Images
and Patterns
, pp. 733–740.
Taira, H., Y. Inoue, A. Torii, and M. Okutomi, 2015. Robust feature
matching for distorted projection by spherical cameras,
Information Processing Society of Japan Transactions on
Computer Vision and Applications
, pp. 84–88.
Torii, A., M. Havlena, and T. Pajdla, 2009. From Google Street View
to 3D city models,
Proceedings of the IEEE 12
th
International
Computer Vision Workshop
.
Tseng, Y.H.,Y.C. Chen, and K.Y. Lin, 2016. Bundle adjustment of
spherical images acquired with a portable panoramic image
mapping system (PPIMS),
Photogrammetric Engineering &
Remote Sensing
, 82:935–943.
Tuytelaars, T., and K. Mikolajczyk, 2007. Local invariant feature
detectors: A survey,
Foundations and Trends in Computer
Graphics and Vision
, 3(3):177–280.
32
January 2018
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
I...,22,23,24,25,26,27,28,29,30,31 33,34,35,36,37,38,39,40,41,42,...54
Powered by FlippingBook