LBenchmarks is a MATLAB framework for testing image feature detectors and descriptors. The latest version can be downloaded here.
If you use this project in your work, please cite it as:
K. Lenc, V. Gulshan, and A. Vedaldi, VLBenchmarks,
http://www.vlfeat.org/benchmarks/, 2012. BibTeX
This project is sponsored by the PASCAL Harvest programme as part of this project. VLBenchmkar is a sibling of the VLFeat Library, which it uses as suppot, but is otherwise independent of it.
The authors would like to thank Andrew Zisserman, Jiri Matas, Krystian Mikolajczyk, Tinne Tuytelaars, and Cordelia Schmid for helpful discussion and supports.
Overview
VLBechmarks is a MATLAB framework to evaluate feature detector and descriptors automatically. Benchmarking your own features is as simple as writing a single wrapper class. Then VLBenchmarks takes care of downloading the required benchmarking data from the Internet and running the evaluation(s). The framework ships with wrappers for a number of publicly available features to enable comparing to them easily. VLBenchmarks has a number of functionalities, such as caching of intermediate results, that allow running benchmarks efficiently.
The current version of VLBechmarks implements:
- The feature extractor repeatability of [1].
- The descriptor matching score of [1].
- A new retrieval-based test based on the retrieval method of [2].
The code is distributed under the permissive MIT license.
Changes
- 1.0-beta
- (7/10/2012) Initial release.
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