Andrea Vedaldi, Ph.D. (vedaldi@robots.ox.ac.uk)
Research Fellow, Oxford University, Visual Geometry Group - map

Tel. +44 1865 283057.


10/22/2010
VLFeat wins the ACM Multimedia Open Source Software Competition
9/5/2010
VLFeat presented at the ECCV10 Tutorial on Computer Vision and 3D Perception for Robotics
6/11/2010
CVPR10 Tutorial on Open Source Vision Software.
6/11/2010
New contributed Python interface to siftpp.
5/24/2010
VLFeat 0.9.8 relased.

Research interests: Object and category classification and detection. Invarian visual features. Structured output learning.

VLFeat. The VLFeat open source library implements popular computer vision algorithms in a simple-to-use package with MATLAB bindings. It bundles algorithms such as SIFT, MSER, k-means, hierarchical k-means, kd-trees, agglomerative information bottleneck, quick shift.

Winner of the ACM Multimedia Open Source Software Competition (2010).




CVPR 2010 Poster


Paper

Efficient additive kernels: The homogeneous kernel map. We introduce closed-form finite dimensional feature maps approximating the additive kernels (intersection, Hellinger’s, χ2, Jensen-Shannon, ...). By adding onle line to your code you can use non-linear additive kernels as if they were linear, with vastly improved training and testing speed and compactness of the resulting models (code).