Elements of information theory
Elements of information theory
International Journal of Computer Vision
Spectral covariance and fuzzy regions for image indexing
Machine Vision and Applications
Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
Perceptual Metrics for Image Database Navigation
Perceptual Metrics for Image Database Navigation
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Color Histogram Indexing for Quadratic Form Distance Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A continuous probabilistic framework for image matching
Computer Vision and Image Understanding
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Region Correspondence for Image Matching via EMD Flow
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Integrated spatial and feature image query
Multimedia Systems
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Image similarity search with compact data structures
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Context-Based Segmentation of Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Multimedia Tools and Applications
Region and constellations based categorization of images with unsupervised graph learning
Image and Vision Computing
Hybrid Dynamical Models of Human Motion for the Recognition of Human Gaits
International Journal of Computer Vision
Computer Vision and Image Understanding
Image retrieval with segmentation-based query
AMR'06 Proceedings of the 4th international conference on Adaptive multimedia retrieval: user, context, and feedback
A Bayesian framework for image segmentation with spatially varying mixtures
IEEE Transactions on Image Processing
A relevance feedback approach for content based image retrieval using gaussian mixture models
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Hierarchical partitions for content image retrieval from large-scale database
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
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The content of an image can be summarized by a set of homogeneous regions in an appropriate feature space. When exact shape is not important, the regions can be represented by simple "blobs." Even for similar images, the blob representation of the two images might vary in shape, position, the number of blobs, and the represented features. In addition, separate blobs in one image might correspond to a single blob in the other image and vice versa. In this paper we present the BlobEMD framework as a novel method to compute the dissimilarity of two sets of blobs while allowing for context-based adaptation of the image representation. This results in representations that represent well the original images but at the same time are best aligned with respect to the representations of the context images. Similarly, we can perform image segmentation where the segmentation of an image is guided by a reference image. This novel approach makes segmentation a context-based task. We compute the blobs by using Gaussian mixture modeling and use the Earth mover's distance (EMD) to compute both the dissimilarity of the images and the flow-matrix of the blobs between the images. The Blob-EMD flow-matrix is used to find optimal correspondences between source and target image representations and to adapt the representation of the source image to that of the target image. This allows for similarity measures between images that are insensitive to the segmentation process and to different levels of details of the representation. We show applications of this method for content-based image retrieval, image segmentation, and matching models of heavily dithered images with models of full resolution images.