Coarse-to-fine strategy for efficient cost-volume filtering


Cost-volume filtering is one of the most widely known techniques to solve general multi-label problems, however it is problematically inefficient when the label space size is extremely large. This paper presents a coarse-to-fine strategy of the cost-volume filtering that handles efficiently and accurately multi-label problems with a large label space size. Based upon the observation that true labels at the same image coordinate of different scales are highly correlated, we truncate unimportant labels for the cost-volume filtering by leveraging the labeling output of lower scales. Experimental results show that our algorithm achieves much higher efficiency than the original cost-volume filtering while enjoying the comparable accuracy to it.

DOI: 10.1109/ICIP.2014.7025770

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@article{Furuta2014CoarsetofineSF, title={Coarse-to-fine strategy for efficient cost-volume filtering}, author={Ryosuke Furuta and Satoshi Ikehata and Toshihiko Yamasaki and Kiyoharu Aizawa}, journal={2014 IEEE International Conference on Image Processing (ICIP)}, year={2014}, pages={3793-3797} }