Revision as of 12:07, 16 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

@@ Line 26: / Line 26: @@
 * [http://en.wikipedia.org/wiki/Scale-invariant_feature_transform Wikipedia article on SIFT], contains several good references
 * [http://homes.esat.kuleuven.be/%7Etuytelaa/ECCV06tutorial.html Tutorial on local invariant features]
-* [http://www.mis.informatik.tu-darmstadt.de/Education/Courses/cv/index.html Lecture notes] on feature detection/matching]
+* [http://www.mis.informatik.tu-darmstadt.de/Education/Courses/cv/index.html Lecture notes] on feature detection/matching
 === Software ===

Difference between revisions of "Historical:SoC2007 project Feature Descriptor"