Local feature based supervised object detection: Sampling, learning and detection strategies

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2011, Pages 2381-2384

  Michel, J ^a   Grizonnet, M ^a   Inglada, J ^a   Malik, J ^b   Bricier, A ^b   Lahlou, O ^b  

^a CNES   (France)

^b C S IGI   (France)

Author keywords

classification; learning; Object detection

Indexed keywords

DESCRIPTORS; HIGH RESOLUTION REMOTE SENSING IMAGERY; LEARNING; LOCAL FEATURE; NATURAL IMAGES; NEGATIVE EXAMPLES; OBJECT DETECTION; OPERATIONAL STATE; PLANE DETECTION; PROCESSING CHAIN;

GEOLOGY; REMOTE SENSING;

OBJECT RECOGNITION;

EID: 80955124012     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2011.6049689     Document Type: Conference Paper

References (13)

1. P. F. Felzenszwalb, R. B. Girshick, and D. McAllester, "Discriminatively trained deformable part models, release 4," http://people.cs.uchicago.edu/ pff/latent-release4/.
2. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. IEEE, 2005, vol. 1, pp. 886-893.
3. J. Inglada and J. Michel, "Qualitative spatial reasoning for high-resolution remote sensing image analysis," IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 2, pp. 599-612, Feb. 2009.
4. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Citeseer, 2001, vol. 1.
5. P. Viola and M. Jones, "Robust real-time object detection," International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, 2002.
6. J. Inglada, "Automatic recognition of man-made objects in high resolution optical remote sensing images by SVM classification of geometric image features," ISPRS journal of photogrammetry and remote sensing, vol. 62, no. 3, pp. 236-248, 2007. (Pubitemid 47043389)
7. Jan Flusser, "On the independence of rotation moment invariants," Pattern Recognition, vol. 33, pp. 1405-1410, 2000.
8. S. Derrode and F. Ghorbel, "Robust and efficient Fourier- Mellin transform approximations for gray-level image reconstruction and complete invariant description," Computer Vision and Image Understanding, vol. 83, no. 1, pp. 57-78, 2001. (Pubitemid 32863880)
9. R.M. Haralick, K. Shanmugam, and I.H. Dinstein, "Textural features for image classification," IEEE Transactions on systems, man and cybernetics, vol. 3, no. 6, pp. 610-621, 1973.
10. J. Chen, S. Shan, C. He, G. Zhao, M. Pietik "ainen, X. Chen, andW. Gao, "WLD: A robust local image descriptor," IEEE transactions on pattern analysis and machine intelligence, pp. 1705-1720, 2009.
11. A. Abdullah, R.C. Veltkamp, and M.A. Wiering, "An Ensemble of Deep Support Vector Machines for Image Categorization," in 2009 International Conference of Soft Computing and Pattern Recognition. IEEE, 2009, pp. 301-306.
12. D. Commaniciu, "Mean Shift: A Robust Approach Toward Feature Space Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 603-619, May 2002.
13. J. Michel, C. Valladeau, and J. Inglada, "Focus pre-processing chain for object detection in high resolution remote sensing images," in Geoscience and Remote Sensing Symposium, 2009 IEEE International, IGARSS 2009. IEEE, 2010, vol. 2.