: A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual Clustering.
Hyeon JeonGhulam Jilani QuadriHyunwook LeePaul RosenDanielle Albers SzafirJinwook SeoPublished in: IEEE Trans. Vis. Comput. Graph. (2024)
Keyphrases
- clustering algorithm
- intra cluster
- data clustering
- inter cluster
- hierarchical clustering
- clustering method
- cluster analysis
- overlapping clusters
- k means
- low level
- clustering framework
- data points
- unsupervised clustering
- visual perception
- cluster validation
- cluster membership
- cluster centers
- disjoint clusters
- visual features
- clustering approaches
- supervised clustering
- constrained clustering
- human visual
- visual information
- human vision
- clustering scheme
- density based clustering algorithm
- clustering result
- model based clustering
- cluster validity
- clustering procedure
- hierarchical clustering algorithm
- similarity measure
- evolutionary clustering
- spectral clustering
- similar objects
- clustering analysis
- clustering quality
- agglomerative hierarchical clustering
- arbitrary shape
- subspace clustering
- dissimilarity measure
- distance measure
- image segmentation
- high level
- cluster labels
- instance level constraints
- unsupervised learning
- density based clustering
- cluster structure
- document clustering
- neighborhood information
- feature space
- visual input
- semi supervised clustering
- image quality assessment
- self organizing maps
- perceptual grouping
- perceptual information
- categorical data
- validity measures
- human perception
- quality measures