Vlfeat
Authors:
Open Access
- 25 October 2010
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 1469-1472
Abstract
VLFeat is an open and portable library of computer vision algorithms. It aims at facilitating fast prototyping and reproducible research for computer vision scientists and students. It includes rigorous implementations of common building blocks such as feature detectors, feature extractors, (hierarchical) k-means clustering, randomized kd-tree matching, and super-pixelization. The source code and interfaces are fully documented. The library integrates directly with MATLAB, a popular language for computer vision research. © 2010 ACMKeywords
This publication has 7 references indexed in Scilit:
- Efficient additive kernels via explicit feature maps2010
- On feature combination for multiclass object classification2009
- Quick Shift and Kernel Methods for Mode Seeking2008
- Image Classification using Random Forests and Ferns2007
- Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories2006
- Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 2004
- Robust Wide Baseline Stereo from Maximally Stable Extremal Regions2002