Revision as of 21:06, 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.

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

Project Schedule

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/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

Students planning to apply

Pedro Alonso Ferrer

@@ Line 1: / Line 1: @@
+See [[SoC 2007 overview]] for usage hints and a page list.
 = Robust local feature detector and descriptor =
@@ Line 13: / Line 16: @@
 * Integration of the library into [[hugin]]
-== Timeline ==
+== Project Schedule ==
+* 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/available ressources ==
@@ Line 34: / Line 54: @@
 License: LGPL
+== Students planning to apply ==
+* [[User:pedro|Pedro Alonso Ferrer]]
 [[Category:Community:Project]]

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