A texture thesaurus for browsing large aerial photographs
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Categorizing Visual Contents by Matching Visual ``Keywords''
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
A General Framework for Object Detection
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing faces with PCA and ICA
Computer Vision and Image Understanding - Special issue on Face recognition
Journal of VLSI Signal Processing Systems - Special issue on signal processing and neural networks for bioinformatics
Journal of Cognitive Neuroscience
Matching and retrieval based on the vocabulary and grammar of color patterns
IEEE Transactions on Image Processing
Robust information-theoretic clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
RIC: Parameter-free noise-robust clustering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Diffusion maps-based image clustering
Proceedings of the 2006 international workshop on Research issues in digital libraries
Reference-based indexing for metric spaces with costly distance measures
The VLDB Journal — The International Journal on Very Large Data Bases
Human action analysis, annotation and modeling in video streams based on implicit user interaction
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Human action annotation, modeling and analysis based on implicit user interaction
Multimedia Tools and Applications
Image clustering using multimodal keywords
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
QuMinS: Fast and scalable querying, mining and summarizing multi-modal databases
Information Sciences: an International Journal
Hi-index | 0.00 |
Given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? For example, given a large collection of retinal images from several different experimental conditions (normal, detached, reattached, etc.), how can data mining help biologists focus on important regions in the images or on the differences between different experimental conditions? If the images were text documents, we could find the main terms and concepts for each condition by existing IR methods (e.g., tf/idf and LSI). We propose something analogous, but for the much more challenging case of an image collection: We propose to automatically develop a visual vocabulary by breaking images into n 脳 n tiles and deriving key tiles ("ViVos") for each image and condition. We experiment with numerous domain-independent ways of extracting features from tiles (color histograms, textures, etc.), and several ways of choosing characteristic tiles (PCA, ICA). We perform experiments on two disparate biomedical datasets. The quantitative measure of success is classification accuracy: Our "ViVos" achieve high classification accuracy (up to 83% for a nine-class problem on feline retinal images). More importantly, qualitatively, our "ViVos" do an excellent job as "visual vocabulary terms": they have biological meaning, as corroborated by domain experts; they help spot characteristic regions of images, exactly like text vocabulary terms do for documents; and they highlight the differences between pairs of images.