Machine learning and kernel methods for computer vision
Dec 5, 2008 17552 views 
en-fr
en-zh
en
en-pt
en-sl
en-de
en-es
0.25
0.5
0.75
1.25
1.5
1.75
2
Kernel methods are a new theoretical and algorithmic framework for machine learning. By representing data through well defined dot-products, referred to as kernels, they allow to use classical linear supervised machine learning algorithms to non linear settings and to non vectorial data. A major issue when applying these methods to image processing or computer vision is the choice of the kernel. I will present recent advances in the design of kernels for images that take into account the natural structure of images.