Automated species detection: An experimental approach to kelp detection from sea-floor AUV images

Australasian Conference on Robotics and Automation, ACRA

Volumn , Issue , 2012, Pages

  Bewley, M S ^a   Douillard, B ^a   Nourani Vatani, N ^a   Friedman, A ^a   Pizarro, O ^a   Williams, S B ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED DETECTION; AUTONOMOUS UNDERWATER VEHICLES (AUV); ECKLONIA RADIATA; EXPERIMENTAL APPROACHES; EXPERIMENTAL STUDIES; LOCAL BINARY PATTERNS; LOCAL IMAGE FEATURES; MARINE SCIENTISTS;

AUTOMATION; PRINCIPAL COMPONENT ANALYSIS; ROBOTICS;

AUTONOMOUS UNDERWATER VEHICLES;

EID: 84879987630     PISSN: 14482053     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. N.S. Barrett, L. Meyer, N. Hill, and P.H. Walsh. Methods for the processing and scoring of AUV digital imagery from South Eastern Tasmania. Technical Report 11560, University of Tasmania, August 2011.
2. N.S. Barrett, J. Seiler, T. Anderson, S. Williams, S. Nichol, and S.N. Hill. Autonomous underwater vehicle (AUV) for mapping marine biodiversity in coastal and shelf waters: Implications for marine management. In IEEE OCEANS, pages 1-6, May 2010.
3. O. Beijbom, P.J. Edmunds, D.I. Kline, B.G. Mitchell, and D. Kriegman. Automated annotation of coral reef survey images. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), page 1170, 2012.
4. C. M Bishop. Pattern recognition and machine learning. Springer Science+Business Media, LLC, New York, 2006.
5. M. Bryson, M. Johnson-Roberson, O.R. Pizarro, and S. B. Williams. Repeatable robotic surveying of marine benthic habitats for monitoring long-term change. In Robotics: Science and Systems Conference (RSS), July 2012.
6. R. Clement, M. Dunbabin, and G. Wyeth. Toward robust image detection of crown-of-thorns starfish for autonomous population monitoring. In The Australasian Conference on Robotics and Automation (ACRA), 2005.
7. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 886 - 893, June 2005.
8. A. Denuelle and M. Dunbabin. Kelp detection in highly dynamic environments using texture recognition. In The Australasian Conference on Robotics & Automation (ACRA), December 2010.
9. V. Di Gesu, F. Isgr, D. Tegolo, and E. Trucco. Finding essential features for tracking starfish in a video sequence. In International Conference on Image Analysis and Processing, pages 504 - 509, 2003.
10. M. Dunbabin and L. Marques. Robots for environmental monitoring: Significant advancements and applications. Robotics Automation Magazine, IEEE, 19(1):24 - 39, March 2012.
11. I Fogel and D Sagi. Gabor filters as texture discriminator. Biological Cybernetics, 61:103 - 113, 1989.
12. A. Friedman, D. Steinberg, O. Pizarro, and S. B. Williams. Active learning using a variational dirichlet process model for pre-clustering and classification of underwater stereo imagery. In Intelligent Robots and Systems (IROS), pages 1533 - 1539, 2011.
13. M. Hall-Beyer. The GLCM tutorial home page. http://www.fp.ucalgary.ca/ mhallbey/tutorial.htm, February 2007.
14. R.M. Haralick, K. Shanmugam, and I. Dinstein. Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics, 3(6):610 - 621, November 1973.
15. C.W. Hsu, C.C. Chang, and C.J. Lin. A practical guide to support vector classification, April 2010.
16. Y.M. Huang and S.X. Du. Weighted support vector machine for classification with uneven training class sizes. In International Conference on Machine Learning and Cybernetics, volume 7, pages 4365 - 4369, August 2005.
17. M. Johnson-Roberson, O.R. Pizarro, S.B. Williams, and I. Mahon. Generation and visualization of large-scale three-dimensional reconstructions from underwater robotic surveys. Journal of Field Robotics, 27(1):21 - 51, 2010.
18. K. E Kohler and S. M Gill. Coral point count with excel extensions (CPCe): a visual basic program for the determination of coral and substrate coverage using random point count methodology. Computers & Geosciences, 32(9):1259 - 1269, 2006.
19. M.S.A. Marcos, M Soriano, and C. Saloma. Classification of coral reef images from underwater video using neural networks. Optics Express, 13(22):8766 - 8771, 2005.
20. A.Y. Ng. Preventing "overfitting" of cross-validation data. In International Conference on Machine Learning (ICML), pages 245 - 253, 1997.
21. T. Ojala, M. Pietikaeinen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):971 - 987, 2002.
22. O.R. Pizarro, S.B. Williams, and J. Colquhoun. Topic-based habitat classification using visual data. pages 1-8, May 2009.
23. P. Rigby, O.R. Pizarro, and S.B. Williams. Toward adaptive benthic habitat mapping using gaussian process classification. Journal of Field Robotics, 27(6):741 - 758, 2010.
24. C. Shan, S. Gong, and P.W. McOwan. Robust facial expression recognition using local binary patterns. In IEEE International Conference on Image Processing, pages 4 - 7. IEEE, 2005.
25. D. Smith and M. Dunbabin. Automated counting of the northern pacific sea star in the derwent using shape recognition. In The Australasian Conference on Robotics & Automation (ACRA), pages 500 - 507, December 2007.
26. M. Soriano, S. Marcos, C. Saloma, M. Quibilan, and P. Alino. Image classification of coral reef components from underwater color video. volume 2, pages 1008-1013, 2001.
27. M. Soriano, T. Ojala, and M. Pietikainen. Robustness of local binary pattern operators to tilt compensated textures. Workshop on Texture Analysis in Machine Vision Oulu Finland, 1999.
28. D. Steinberg, A. Friedman, O.R. Pizarro, and S.B. Williams. A bayesian nonparametric approach to clustering data from underwater robotic surveys. In International Symposium on Robotics Research (ISRR), August 2011.
29. R.B. Taylor. Seasonal variation in assemblages of mobile epifauna inhabiting three subtidal brown seaweeds in northeastern new zealand. Hydrobiologia, 361(1):25-35, 1997.
30. S.B. Williams, P. Newman, G. Dissanayake, and H. Durrant-Whyte. Autonomous underwater simultaneous localisation and map building. In International Conference on Robotics and Automation (ICRA), volume 2, pages 1793-1798, 2000.
31. S.B. Williams, O. Pizarro, M.V. Jakuba, D. Steinberg, A. Friedman, and N. Ahsan. Autonomous underwater vehicle monitoring of benthic reference sites. In Intelligent Robots and Systems (IROS), August 2010.
32. S.B. Williams, O.R. Pizarro, M. Jakuba, and N.S. Barrett. AUV benthic habitat mapping in south eastern Tasmania. In Andrew Howard, Karl Iagnemma, and Alonzo Kelly, editors, Field and Service Robotics, volume 62, pages 275 - 284. 2010.
33. S.B. Williams, O.R. Pizarro, M.V. Jakuba, C.R. Johnson, N.S. Barrett, R.C. Babcock, G.A. Kendrick, P.D. Steinberg, A.J. Heyward, P.J. Doherty, I. Mahon, M. Johnson-Roberson, D. Steinberg, and A. Friedman. Monitoring of benthic reference sites: Using an autonomous underwater vehicle. Robotics and Automation Magazine, IEEE, 19(1):73 - 84, March 2012.