The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.20.

Author - Peter Corke

Peter Corke

Peter Corke is a professor of robotic vision at Queensland University of Technology, and director of the ARC Centre of Excellence for Robotic Vision. His research is concerned with enabling robots to see, and the application of robots to mining, agriculture and environmental monitoring. Link

Category: Software
Posted 08 May 2017

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