Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation
Yutian Chen, Andrew E. Gelfand, Charless C. Fowlkes, Max Welling · 2011
We present a new method to combine possibly inconsistent locally (piecewise) trained conditional models p(yα|xα) into pseudo-samples from a global model. Our method does not require training of a CRF, but instead generates samples by iterating forward a weakly chaotic dynamical system. The new method is illustrated on image segmentation tasks where classifiers based on local appearance cues are combined with pairwise boundary cues.