Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
—In partitioning, clustering, and grouping problems, a typical goal is to group together similar objects, or pixels in the case of image processing. At the same time, another goa...