On the completeness of coding with image features

British Machine Vision Conference, BMVC 2009 - Proceedings

Volumn , Issue , 2009, Pages

  Förstner, Wolfgang ^a   Dickscheid, Timo ^a   Schindler, Falko ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DETECTORS; ENTROPY; FEATURE EXTRACTION;

ENTROPY DENSITY; ENTROPY DISTRIBUTION; HELLINGER DISTANCE; IMAGE FEATURES; IMAGE INFORMATION; KEY-POINT DETECTORS; LOCAL FEATURE EXTRACTION; LOCAL IMAGE STATISTICS;

IMAGE CODING;

EID: 84898842073     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.23.1     Document Type: Conference Paper

References (29)

1. Herbert Bay, Vittorio Ferrari, and Luc Van Gool. Wide-Baseline Stereo Matching with Line Segments. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR'05), Volume 1, pages 329-336, Washington, DC, USA, 2005.
2. Geoffrey M. Davis and Aria Nosratinia. Wavelet-Based Image Coding: An Overview. Applied and Computational Control, Signals, and Circuits, 1:205-269, 1998.
3. T. Dickscheid and W. Förstner. Evaluating the Suitability of Feature Detectors for Automatic Image Orientation Systems. In 7th International Conference on Computer Vision Systems (ICVS'09), Liege, Belgium, 2009.
4. W. Förstner. Image Preprocessing for Feature Extraction in Digital Intensity, Color and Range Images. In Geomatic Methods for the Analysis of Data in Earth Sciences, Volume 95/2000 of Lecture Notes in Earth Sciences, pages 165-189. Springer, 1998.
5. W. Förstner, T. Dickscheid, and F. Schindler. Detecting Interpretable and Accurate Scale-Invariant Keypoints. In 12th IEEE International Conference on Computer Vision (ICCV'09), Kyoto, Japan, 2009.
6. Wolfgang Förstner. A Framework for Low Level Feature Extraction. In Third European Conference on Computer Vision (ECCV'94), volume III, pages 383-394, Stockholm, Sweden, 1994. ISBN 0-387-57957-5.
7. Wolfgang Förstner and Eberhard Gülch. A Fast Operator for Detection and Precise Location of Distinct Points, Corners and Centres of Circular Features. In ISPRS Conference on Fast Processing of Photogrammetric Data, pages 281-305, Interlaken, June 1987.
8. Jacopo Grazzini, Antonio Turiel, and Hussein Yahia. Entropy Estimation and Mul-tiscale Processing in Meteorological Satellite Images. International Conference on Pattern Recognition (ICPR'02), 3:30764, 2002.
9. A. Haja, B. Jähne, and S. Abraham. Localization Accuracy of Region Detectors. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'08), June 2008. ISSN 1063-6919.
10. C. Harris and M. J. Stephens. A Combined Corner and Edge Detector. In Alvey Vision Conference, pages 147-152, 1988.
11. Mike Heath, Sudeep Sarkar, Thomas Sanocki, and Kevin Bowyer. Comparison of Edge Detectors: A Methodology and Initial Study. IEEE Conference on Computer Vision and Pattern Recognition (CVPR'96), 0:143, 1996.
12. C. Vignat J.-F. Bercher. Estimating the Entropy of a Signal with Applications. IEEE Transactions on Signal Processing, 48(6), June 2000.
13. Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06), pages 2169-2178, Washington, DC, USA, 2006.
14. Fei-Fei Li and Pietro Perona. A Bayesian Hierarchical Model for Learning Natural Scene Categories. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR'05), Volume 2, pages 524-531, Washington, DC, USA, 2005. IEEE Computer Society.
15. Tony Lindeberg. Feature Detection with Automatic Scale Selection. International Journal of Computer Vision, 30(2):79-116, 1998.
16. Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawrence Zitnick, and William T. Freeman. Automatic estimation and removal of noise from a single image. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):299-314, 2008.
17. David G. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60(2):91-110, 2004.
18. David Marr. Vision: A Computational Investigation Into the Human Representation and Processing of Visual Information. W. H. Freeman, San Francisco, 1982.
19. J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust Wide Baseline Stereo from Maximally Stable Extremal Regions. Image and Vision Computing, 22:761-767, 2004.
20. Krystian Mikolajczyk and Cordelia Schmid. Scale and Affine Invariant Interest Point Detectors. International Journal of Computer Vision, 60(1):63-86, 2004.
21. Krystian Mikolajczyk, Tinne Tuytelaars, Cordelia Schmid, Andrew Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and Luc Van Gool. A Comparison of Affine Region Detectors. International Jounal of Computer Vision, 65(1/2):43-72, 2005.
22. P. Moreels and P. Perona. Evaluation of Features Detectors and Descriptors based on 3D objects. In International Journal of Computer Vision, 2006.
23. David Mumford. Empirical Statistics and Stochastic Models for Visual Signals. In S. Haykin, J.C. Principe, T.J. Sejnowski, and J. McWhirter, editors, New Directions in Statistical Signal Processing: From Systems to Brain. MIT Press, Cambridge, MA, 2005.
24. B. A. Olshausen and D. J. Field. Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images. Nature, 381(6583):607-609, June 1996.
25. Claude E. Shannon. A Mathematical Theory of Communication. Technical report, Bell System Technical Journal, 1948.
26. Bill Triggs. Detecting Keypoints with Stable Position, Orientation, and Scale under Illumination Changes. In 8th European Conference on Computer Vision (ECCV'04), pages 100-113, 2004.
27. Tinne Tuytelaars and Krystian Mikolajczyk. Local Invariant Feature Detectors: A Survey. Now Publishers Inc., Hanover, MA, USA, 2008.
28. Tinne Tuytelaars and Luc Van Gool. Matching Widely Separated Views Based on Affine Invariant Regions. International Journal of Computer Vision, 59(1):61-85, 2004.
29. B. Zeisl, P. Georgel, F. Schweiger, E. Steinbach, and N. Navab. Estimation of Location Uncertainty for Scale Invariant Feature Points. In British Machine Vision Conference, London, UK, 2009.