Automatic extraction of face-features
Pattern Recognition Letters
Human face profile recognition by computer
Pattern Recognition
IBM Journal of Research and Development
PROBE Spatial Data Modeling and Query Processing in an Image Database Application
IEEE Transactions on Software Engineering
An Efficient Pictorial Database System for PSQL
IEEE Transactions on Software Engineering
An Intelligent Image Database System
IEEE Transactions on Software Engineering
Extending a DBMS for Geographic Applications
Proceedings of the Fifth International Conference on Data Engineering
Semantic Queries with Pictures: The VIMSYS Model
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
A Real-Time Matching System for Large Fingerprint Databases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using semantic contents and WordNet in image retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient resource selection in distributed visual information systems
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
An error-based conceptual clustering method for providing approximate query answers
Communications of the ACM - Electronic supplement to the December issue
Information retrieval on the web
ACM Computing Surveys (CSUR)
Automatic Video Database Indexing and Retrieval
Multimedia Tools and Applications
Supporting Content-Based Retrieval in Large Image Database Systems
Multimedia Tools and Applications
Multimedia Tools and Applications
Multimedia Tools and Applications
Multimedia Information Systems
IEEE MultiMedia
A Knowledge-Based Approach for Retrieving Images by Content
IEEE Transactions on Knowledge and Data Engineering
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
Content-Based Indexing of Multimedia Databases
IEEE Transactions on Knowledge and Data Engineering
Knowledge-Based Image Retrieval with Spatial and Temporal Constructs
IEEE Transactions on Knowledge and Data Engineering
Fast and Effective Retrieval of Medical Tumor Shapes
IEEE Transactions on Knowledge and Data Engineering
Data Resource Selection in Distributed Visual Information Systems
IEEE Transactions on Knowledge and Data Engineering
A Survey on Content-Based Retrieval for Multimedia Databases
IEEE Transactions on Knowledge and Data Engineering
Multilevel Filtering for High-Dimensional Image Data: Why and How
IEEE Transactions on Knowledge and Data Engineering
SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data
IEEE Transactions on Knowledge and Data Engineering
Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
System for Medical Image Retrieval: The MIMS Model
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Hierarchical Content Description and Object Formation by Learning
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Segmentation based coding of human face images for retrieval
Signal Processing
Robust visual similarity retrieval in single model face databases
Pattern Recognition
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The complex nature of two-dimensional image data has presented problems for traditional information systems designed strictly for alphanumeric data. Systems aimed at effectively managing image data have generally approached the problem from two different views: They either possess a strong database component with little image understanding, or they serve as an image repository for computer vision applications, with little emphasis on the image retrieval process. A general architecture for visual information-management systems (VIMS), which combine the strengths of both approaches, is presented. The system utilizes computer vision routines for both insertion and retrieval and allows easy query-by-example specifications. The vision routines are used to segment and evaluate objects based on domain-knowledge describing the objects and their attributes. The vision system can then assign feature values to be used for similarity-measures and image retrieval. A VIMS developed for face-image retrieval is presented to demonstrate these ideas.