Speeded up robust features: Difference between revisions
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* [http://www.vision.ee.ethz.ch/~surf/eccv06.pdf First publication of Speeded Up Robust Features (2006)] |
* [http://www.vision.ee.ethz.ch/~surf/eccv06.pdf First publication of Speeded Up Robust Features (2006)] |
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* [ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf Revised publication of SURF (2008)] |
* [ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf Revised publication of SURF (2008)] |
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*[http://www.mitov.com/html/visionlab.html VisionLab] - [[Embarcadero Delphi|Delphi]], [[C++]] and [[.NET Framework|.NET]] free for educational purposes library containing SURF component. |
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[[Category:Computer vision]] |
[[Category:Computer vision]] |
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Revision as of 06:38, 1 January 2010
| Feature detection |
|---|
| Edge detection |
| Corner detection |
| Blob detection |
| Ridge detection |
| Hough transform |
| Structure tensor |
| Affine invariant feature detection |
| Feature description |
| Scale space |
SURF (Speeded Up Robust Features) is a robust image detector & descriptor, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images. As basic image features it uses a Haar wavelet approximation of the determinant of Hessian blob detector.
Implementations
- Original implementation (closed source)
- OpenSURF (open source) implementation with detailed documentation and reference paper (C++, C#, Linux)
- OpenCV SURF (open source) implementation of SURF feature extraction (OpenCV 2.0)
- GPU SURF (closed source) a GPU Implementation
- libmv SURF (open source) implementation of extraction and matching.
- Dlib C++ Library (open source) implementation of SURF feature extraction
- Pan-o-matic (open source) software which includes an implementation of the SURF algorithm
- C# SURF plugin for Multi-Agent Serving System (open source) implementation of extraction and matching.
- JavaSurf (open source) java implementation (platform independent)
- ImageJ SURF (open source) SURF implementation as ImageJ plugin with a convenient GUI and output of statistics (platform independent).
See also
- Scale-invariant feature transform
- Gradient Location and Orientation Histogram
- LESH - Local Energy based Shape Histogram
- Blob detection
- Feature detection (computer vision)
References
- Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool "SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359, 2008
- Christopher Evans "Notes on the OpenSURF Library", MSc Computer Science, University of Bristol
External links
- Website of SURF: Speeded Up Robust Features
- MATLAB interface with examples
- First publication of Speeded Up Robust Features (2006)
- Revised publication of SURF (2008)
- VisionLab - Delphi, C++ and .NET free for educational purposes library containing SURF component.