Exemplar Cut

Jimei Yang, Yi-Hsuan Tsai and Ming-Hsuan Yang
Electrical Engineering and Computer Science, University of California at Merced

Abstract: We present a hybrid parametric and nonparametric algorithm, exemplar cut, for generating class-specific object segmentation hypotheses. For the parametric part, we train a pylon model on a hierarchical region tree as the energy function for segmentation. For the nonparametric part, we match the input image with each exemplar by using regions to obtain a score which augments the energy function from the pylon model. Our method thus generates a set of highly plausible segmentation hypotheses by solving a series of exemplar augmented graph cuts. Experimental results on the Graz and PASCAL datasets show that the proposed algorithm achieves favorable segmentation performance against the state-of-the-art methods in terms of visual quality and accuracy.
Jimei Yang, Yi-Hsuan Tsai and Ming-Hsuan Yang "Exemplar Cut," ICCV, 2013. (PDF) (Sup) (Poster) (Code)