Andrea Vedaldi, Ph.D. (firstname.lastname@example.org)
- VLFeat wins the ACM Multimedia Open Source Software Competition
- VLFeat presented at the ECCV10 Tutorial on Computer Vision and 3D Perception for Robotics
- CVPR10 Tutorial on Open Source Vision Software.
- New contributed Python interface to siftpp.
- 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).
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).