Efficient Implementation of the Fuzzy c-Means Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Eigendecomposition Approach to Weighted Graph Matching Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elements of information theory
Elements of information theory
Interpolation artefacts in mutual information-based image registration
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
On Affine Invariant Clustering and Automatic Cast Listing in Movies
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Estimation of entropy and mutual information
Neural Computation
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Automatic Detection and Clustering of Actor Faces based on Spectral Clustering Techniques
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting multiple features in the CID Color Space for face recognition
IEEE Transactions on Image Processing
Joint manifold distance: a new approach to appearance based clustering
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Optimization of mutual information for multiresolution image registration
IEEE Transactions on Image Processing
Probabilistic multiple face detection and tracking using entropy measures
IEEE Transactions on Circuits and Systems for Video Technology
Information theory-based shot cut/fade detection and video summarization
IEEE Transactions on Circuits and Systems for Video Technology
Hi-index | 0.00 |
This paper investigates facial image clustering, primarily for movie video content analysis with respect to actor appearance. Our aim is to use novel formulation of the mutual information as a facial image similarity criterion and, by using spectral graph analysis, to cluster a similarity matrix containing the mutual information of facial images. To this end, we use the HSV color space of a facial image (more precisely, only the hue and saturation channels) in order to calculate the mutual information similarity matrix of a set of facial images. We make full use of the similarity matrix symmetries, so as to lower the computational complexity of the new mutual information calculation. We assign each row of this matrix as feature vector describing a facial image for producing a global similarity criterion for face clustering. In order to test our proposed method, we conducted two sets of experiments that have produced clustering accuracy of more than 80%. We also compared our algorithm with other clustering approaches, such as the k-means and fuzzy c-means (FCM) algorithms. Finally, in order to provide a baseline comparison for our approach, we compared the proposed global similarity measure with another one recently reported in the literature.