SIAM Journal on Scientific and Statistical Computing
Algorithm 659: Implementing Sobol's quasirandom sequence generator
ACM Transactions on Mathematical Software (TOMS)
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Determining number of clusters and prototype locations via multi-scale clustering
Pattern Recognition Letters
ACM Computing Surveys (CSUR)
The Topological Structure of Scale-Space Images
Journal of Mathematical Imaging and Vision
Clustering by Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cluster validity methods: part I
ACM SIGMOD Record
Clustering validity checking methods: part II
ACM SIGMOD Record
Linear Scale-Space has First been Proposed in Japan
Journal of Mathematical Imaging and Vision
Journal of Mathematical Imaging and Vision
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Fast Gauss Transform and Efficient Kernel Density Estimation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast nonparametric clustering with Gaussian blurring mean-shift
ICML '06 Proceedings of the 23rd international conference on Machine learning
Gradient Structure of Image in Scale Space
Journal of Mathematical Imaging and Vision
On the number of modes of a Gaussian mixture
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Acquisition of concept descriptions by conceptual clustering
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Scale-Space hierarchy of singularities
DSSCV'05 Proceedings of the First international conference on Deep Structure, Singularities, and Computer Vision
Figure field analysis of linear scale-space image
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Information measures in scale-spaces
IEEE Transactions on Information Theory
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
Scale-based clustering using the radial basis function network
IEEE Transactions on Neural Networks
Engineering Applications of Artificial Intelligence
A clustering based feature selection method in spectro-temporal domain for speech recognition
Engineering Applications of Artificial Intelligence
| Hi-index | 0.00 |
This paper presents a method of the unsupervised discovery of valid clusters using statistics on the modes of the probability density function in scale space. First, a Gaussian scale-space theory is applied to the kernel density estimation to derive the hierarchical relationships among the modes of the probability density function in scale space. The data points are classified into clusters according to the mode hierarchy. Second, the algorithm of cluster discovery is presented. The valid clusters are discovered by testing whether each cluster is distinguishable from spurious clusters obtained from uniformly random points. The statistical hypothesis test for cluster discovery requires distribution forms of annihilation scales of the modes estimated from the uniformly random points. The distribution forms are experimentally shown to be unimodal. Finally, cluster discovery is demonstrated using synthetic data and benchmark data.