Kernel Principal Component Analysis Feature Detection for Underwater Images

Abstract:

• Periodical: Advanced Materials Research (Volumes 129-131)
• Pages: 953-958
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.129-131.953
• Online since: August 2010
• Authors: Ganapathi Padmavathi, M. Muthukumar, Suresh Kumar Thakur
• Keywords: KPCA, KPCA-SIFT, PCA-SIFT, Principal Component Analysis (PCA), SIFT

References

[1] Michael Grabner, Helmut Grabner, and Horst Bischof, Fast approximated SIFT, citeseer. (2001).

[2] Luo Juan, Oubong Gwun, A Comparison of SIFT, PCA-SIFT and SURF, International Journal of Image Processing Vol. 3, Issue 4, P. No. -145-152 year (2009).

[3] Yan Ke1, Rahul Sukthankar2, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors, Citeseerx.

[4] Nattachai Watcharapinchai , Supavadee Aramvith , Supakom Siddhichai and Sanparith Marukatat, Dimensionality Reduction of SIFT using PCA for Object Categorization, 2008 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS2008).

DOI: 10.1109/ispacs.2009.4806729

[5] David G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, P. No. 1-72004.

DOI: 10.1023/b:visi.0000029664.99615.94

[6] Dimitris Achlioptas, Frank McSherry and Bernhard Sch¨olkopf, Sampling Techniques for Kernel Methods, citeceerx (2002).

[7] Liefeng Bo, Cristian Sminchisescu , University of Bonn, Efficient Match Kernels between Sets of Features for Visual Recognition, NIPS Conference (2009).

[8] Silvia Silva da Costa Botelho1 , Paulo Lilles Jorge Drews Junior , Mônica da Silva Figueiredo , Celina Haffele Da Rocha , Gabriel Leivas Oliveira1, Appearance-based odometry and mapping with feature descriptors for underwater robots, Journal of the Brazilian Computer Society, vol. 15 issue (3) P. No. 47-54. year (2009).

DOI: 10.1590/s0104-65002009000300005

[9] Andrzej Śluzek, Retrieval of Relevant Visual Data in Selected Machine Vision Tasks: Examples of Hardwarebased and Software-based Solutions, World Academy of Science, Engineering and Technology, Vol. 56, P. No. 215-220, year (2009).

[10] Josef Sivic and Andrew Zisserman, Video Google: A Text Retrieval Approach to Object Matching in Videos, IEEE International Conference on Computer Vision (ICCV 2003) Vol. 2 year (2003).

DOI: 10.1109/iccv.2003.1238663

[11] Stephen Se, David Lowe, Jim Little, Global Localization using Distinctive Visual Features, IEEE International conference on Intelligent Robots and systems P. No 226- 230 year (2002).

DOI: 10.1109/irds.2002.1041393