A Method of Features Extraction Based on Fisheye Image

Article Preview

Abstract:

In this paper, feature extraction algorithm based on spherical perspective projection model for the matching fisheye image is proposed. The fisheye image is mapped to the image plane through spherical mapping. Then the diffusion equation is formed by convolution of the image projection and spherical Gaussian function. The feature points of image are extracted based on the SIFT at the scale of spherical correlation function. Compared with SURF(Speeded Up Robust Features), more feature points in a shorter time are obtained.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1029-1032

Citation:

Online since:

October 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] L. Meinel, M. Findeisen, M. Hes, A. Apitzsch and G. Hirtz: Automated real-time surveillance for ambient assisted living using an omnidirectional camera, 2014 IEEE International Conference on in Consumer Electronics (ICCE) (2014), pp.396-399.

DOI: 10.1109/icce.2014.6776056

Google Scholar

[2] J. P. Barreto, and D. Kostas: Fundamental matrix for cameras with radial distortion, Tenth IEEE International Conference on Computer Vision, Vol. 1, (2005).

DOI: 10.1109/iccv.2005.103

Google Scholar

[3] X. Qin, S. Li: Finding scale-invariant corner feature from full-view image based on discrete spherical model, 2012 International Conference on Systems and Informatics (ICSAI), (2012).

DOI: 10.1109/icsai.2012.6223422

Google Scholar

[4] In Chinese, J. Zhu, L. Ge, F. Han, N. Liu and B. Zhang: Research on Fisheye Lens Imaging Model Based on the Separated Parameters Calibration. Chinese Journal of Sensors and Actuators, Vol. 7, no. 015 (2013).

Google Scholar

[5] M. M. Fleck: Perspective projection: the wrong imaging model, Department of Computer Science, University of Iowa, (1995) pp.1-27.

Google Scholar

[6] J. Weickert, S. Ishikawa and A. Imiya: Linear scale-space has first been proposed in Japan, Journal of Mathematical Imaging and Vision, Vol. 10, no. 3, (1999) pp.237-252.

DOI: 10.1023/a:1008344623873

Google Scholar

[7] T. Bulow: Spherical diffusion for 3D surface smoothing, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 12, (2004) pp.1650-1654.

DOI: 10.1109/tpami.2004.129

Google Scholar

[8] A. C. Murillo, J. J. Guerrero and C. Sagues: Surf features for efficient robot localization with omnidirectional images, 2007 IEEE International Conference on in Robotics and Automation, (2007) pp.3901-3907.

DOI: 10.1109/robot.2007.364077

Google Scholar