Computer Vision and Image Processing

The OpenSURF Computer Vision Library

The task of finding point correspondences between two images of the same scene or object is an integral part of many machine vision or computer vision systems. The algorithm aims to find salient regions in images which can be found under a variety of image transformations. This allows it to form the basis of many vision based tasks; object recognition, video surveillance, medical imaging, augmented reality and image retrieval to name a few.

OpenSURF C++ (Build 12/04/2012)
This archive contains the latest build of the code in the Repository. This is the original and most widely used open source C++ SURF computer vision library available.
OpenSURF C# (Build 12/04/2012)
The official port of the OpenSURF library for C#. Builds as a dll to allow seamless integration into any computer vision system.
Notes on the OpenSURF Library
This paper contains a detailed analysis of the Speeded Up Robust Features computer vision algorithm along with a breakdown of the OpenSURF implementation. Also contains useful info on machine vision and image processing in general.
OpenSURF Bibtex
Should you wish to reference the OpenSURF library in your work, this bibtex entry contains the information you'll need.
OpenSURF SVN Repository
The most up-to-date way to get the OpenSURF code is from the trunk in the Subversion repository. See the Google Code help section for details on how to checkout code or Contact Me for details.

This section contains links to computer vision papers referencing the OpenSURF library along with the library rewritten in other languages. Among them are comparisons of open source computer vision algorithms along with novel applications to face recognition.

An Evaluation of Open Source SURF Computer Vision Implementations
This paper evaluates the performance of open source SURF computer vision library implementations. Two versions of the OpenSURF library are compared to dlib (based on OpenSURF) and the version included in Pan-o-matic computer vision tool.
A comparison of OpenSURF and the original implementation descriptors
This document is a comparison of the OpenSURF feature descriptor with the original computer vision library written by Herbert Bay. This work was kindly provided by Pablo Fernandez.
SURF-Face: Face Recognition Under Viewpoint Consistency Constraints
Application of the computer vision algorithm to face recognition. References "Notes on the OpenSURF Library".

If you've done any work which is based on or provides a reference to OpenSURF and wish for it to appear in this page, please contact me for details.

Please also link to this page if you have found OpenSURF useful!

Copyright © 2015, Christopher Evans