Difference between revisions of "SoC2007 project Feature Descriptor"
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Latest revision as of 19:06, 9 February 2011
See SoC 2007 overview for usage hints and a page list.
Robust local feature detector and descriptor
Goal: Robust matching of features between multiple images using a Hessian-based detector and a suitable descriptor. A detector and descriptor that takes into account the approximately known distortions will have a much higher matching rate, especially when fisheye or wide angle images are used.
- Implementation of the feature detector and descriptor, and a suitable test suite to verify the correctness of the implementation.
A desired result of the projects would be:
- C or C++ library that implements the detection and description steps.
- An executable for extracting features from image file.
- Test suite to evaluate descriptor on a large amount of images.
- Integration of the library into hugin
- 0w April 9 - Application selection
- Interim Period: Learn more about the project, the literature that is being used to develop it, and build a testing set with ground truth ~200 images. This can be done asking for pictures to the mailing list.
- 0w May 28 - Begin coding for the project
- 1w June 4 - Create all the evaluation software, (mainly available from the website of Krystian Mikolajczyk)
- 3w June 18 - Implement of the algorithm chosen for the detector of feature points on the image.
- July 9: Students upload code to code.google.com/hosting; mentors begin mid-term evaluations
- 7w July 23 - Implementation of the descriptor to match the feature points detected.
- 10w August 13 - Benchmark and code optimization.
- 11w August 20 - Final report (Google Deadline for all student work),students upload code to code.google.com/hosting; mentors begin final evaluations; students begin final program evaluations.
Required knowledge or interest in:
- signal or image processing background
- C or C++ development skills.
- Matlab or octave
Literature about feature detection
- Wikipedia article on SIFT, contains several good references
- Tutorial on local invariant features
- Lecture notes on feature detection/matching
- Framework for testing descriptors
Mentor: Pablo d'Angelo, Herbert Bay, ?