2008 IEEE Conference on Computer Vision and Pattern Recognition
Unsupervised estimation of segmentation quality using nonnegative factorization
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2242-5
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the measure they provide is not explicitly related to segmentation errors. The proposed approach differs from these methods on several important points and has several advantages over them.
Citation:
Roman Sandler, Michael Lindenbaum, "Unsupervised estimation of segmentation quality using nonnegative factorization," cvpr, pp.1-8, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008