Recent Results in Graph Cuts: Illumination-Invariant Tracking and k-Pixel Interactions

Daniel Freedman


Abstract

Over the last few years, techniques based on combinatorial optimization have gained a following in computer vision. In particular, a variety of vision algorithms have been formulated which rely on min-cut / max-flow methods. In this talk, we introduce two new results in this vein. First, we show an application of graph-cut methods to the problem of tracking under large variations in illumination. This is a challenging problem which is relevant for a number of surveillance and military applications. Second, we present new results on sufficient conditions for min-cut optimization of energy functions with k-wise interactions of pixels. These conditions should prove useful in a variety of MRF-style problems.


Maintained by Changki Min