VLFeat is a cross-platform open source collection of vision algorithms with a special focus on visual features (for instance SIFT and MSER) and clustering (k-means, hierarchical k-means, agglomerative information bottleneck). It bundles a MATLAB toolbox, a clean and portable C library and a number of command line utilities. Thus it is possible to use the same algorithm both from MATLAB, the command line, and your own programs.
VLFeat is an effort initiated by Andrea Vedaldi and Brian Fulkerson in 2007, based on previously published software from the same authors.
Andrea Vedaldi received
the Bachelor's degree in Information Engineering from the University
of Padova, Italy, in 2003, and the Master's and Ph.D. degrees in
Computer Science from the University of California - Los Angeles, in
2005 and 2008. He is the recipient of the UCLA outstanding Master's
and Ph.D. awards. In 2008 he joined the Visual Geometry Group at
Oxford University as postdoctoral researcher.
Brian Fulkerson
received his B.S. in Computer Engineering from the University of
California - San Diego in 2004, and his M.S. in Computer Science from
the University of California - Los Angeles in 2006. He is currently
pursuing a Ph.D. in Computer Science at the UCLA Vision Lab.
Part of this work was supported by the UCLA Vision Lab and the Oxford VGG Lab. The authors would like to thank the many colleagues that have contributed to VLFeat by testing and providing helpful suggestions and comments.