Revision as of 16:23, 18 March 2007

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.

Deliverables

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

Timeline

Required/available ressources

Required knowledge or interest in:

• signal or image processing background
• C or C++ development skills.
• Matlab or octave

Ressources

Literature

Literature about feature detection

• Wikipedia article on SIFT, contains several good references
• Tutorial on local invariant features
• Lecture notes on feature detection/matching

Software

• Framework for testing descriptors

Mentor: Pablo d'Angelo, Herbert Bay, ?

License: LGPL