Integrating Local Classifiers through Nonlinear Dynamics on Label Graphs with an Application to Image Segmentation

Yutian Chen, Andrew Gelfand, Charless Fowlkes, Max Welling

Proc. of the International Conference on Computer Vision, 2011.

Abstract

We present a new method to combine possibly inconsistent locally (piecewise) trained conditional models p(y|x) 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.

Cite

@inproceedings{ChenGFW_ICCV_2011, author = {Yutian Chen and Andrew Gelfand and Charless Fowlkes and Max Welling}, title = {Integrating Local Classifiers through Nonlinear Dynamics on Label Graphs with an Application to Image Segmentation}, booktitle = {Proc. of the International Conference on Computer Vision}, year = {2011}, doi = {10.1109/iccv.2011.6126553}, url = {https://doi.org/10.1109/iccv.2011.6126553}, }