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SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Afterword: from this revolution to the next
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CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
A Graph Based Object Description for Information Retrieval in Digital Image and Video Libraries
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
Scenario based dynamic video abstractions using graph matching
Proceedings of the 13th annual ACM international conference on Multimedia
Visual information retrieval: minerva video benchmark
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
A real-time shot cut detector: Hardware implementation
Computer Standards & Interfaces
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Pattern Recognition
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Modeling of echocardiogram video based on views and states
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
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This paper describes a new methodology for image search that is applicable to both image libraries and keyframe search over video libraries. In contrast to previous approaches, which require templates or direct manipulation of low-level image parameters, our search system classifies images into a pre-defined subject lexicon, including terms such as trees and flesh tones. The classification is performed off-line using neural network algorithms. Query satisfaction is performed on-line using only the image tags. Because most of the work is done off-line, this methodology answers queries much more quickly than techniques that require direct manipulation of images to answer the query. We also believe that pre-defined subjects are easier for users to understand when searching programmatic video material. Experiments using keyframes extracted by our video library system show that the methodology gives high-quality query results with fast on-line performance.