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_a10.1007/3-540-40053-2 _2doi |
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_aAdvances in Visual Information Systems _h[electronic resource] : _b4th International Conference, VISUAL 2000, Lyon, France, November 2-4, 2000 Proceedings / _cedited by Robert Laurini. |
250 | _a1st ed. 2000. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2000. |
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300 |
_aXII, 545 p. _bonline resource. |
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_aLecture Notes in Computer Science, _x1611-3349 ; _v1929 |
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505 | 0 | _aGuest Speaker -- The Sentient Map and Its Application to the Macro University E-Learning Environment -- Image Information Systems -- An Image Data Model -- Interaction in Content-Based Image Retrieval: An Evaluation of the State-of-the-Art -- Video Information Systems -- Automatic Video Summary and Description -- Relevance Ranking of Video Data Using Hidden Markov Model Distances and Polygon Simplification -- Video Clustering Using SuperHistograms in Large Archives -- 3-D Camera Movements Tracking and Indexing Based on 2-D Hints Extraction -- Main Mobile Object Detection and Localization in Video Sequences -- Statistical Motion-Based Retrieval with Partial Query -- Experiments in Using Visual and Textual Clues for Image Hunting on the Web -- Guest Speaker -- Visualising Information: A Mosaic of Perspectives -- Visual Querying -- Spatial/Temporal Query Processing for Information Fusion Applications -- Metaphors for Visual Querying of Spatio-Temporal Databases -- About Ambiguities in Visual GIS Query Languages: a Taxonomy and Solutions -- Visualization of Dynamic Spatial Data and Query Results Over Time in a GIS Using Animation -- Color -- Upgrading Color Distributions for Image Retrieval Can We Do Better? -- Color Normalization for Digital Video Processing -- Multimedia Content Filtering, Browsing, and Matching Using MPEG-7 Compact Color Descriptors -- Shape-Based Retrieval -- Shape Description for Content-Based Image Retrieval -- Wavelet-Based Salient Points: Applications to Image Retrieval Using Color and Texture Features -- Matching Shapes with Self-intersections -- Image Databases -- A Novel Approach for Accessing Partially Indexed Image Corpora -- Show Me What You Mean! PARISS: A CBIR-Interface That Learns by Example -- Scale Summarized and Focused Browsing of Primitive Visual Content -- Integrated Browsing and Searching of Large Image Collections -- A Rich Get Richer Strategy for Content-Based Image Retrieval -- MRML: A Communication Protocol for Content-Based Image Retrieval -- An Integrated Multimedia System with Learning Capabilities -- Video Indexing -- Global Motion Fourier Series Expansion for Video Indexing and Retrieval -- Feature Driven Visualization of Video Content for Interactive Indexing -- Conceptual Indexing of Television Images Based on Face and Caption Sizes and Locations -- Image Databases -- SIMPLIcity: Semantics-sensitive Integrated Matching for Picture LIbraries -- Semantic Indexing for Image Retrieval Using Description Logics -- An Iconic and Semantic Content Based Retrieval System for Histological Images -- Image Retrieval -- Image Retrieval by Colour and Texture Using Chromaticity Histograms and Wavelet Frames -- Adaptive Multi-Class Metric Content-Based Image Retrieval -- Integrating Visual and Textual Cues for Image Classification -- Benchmarking -- Evaluating the Performance of Content-Based Image Retrieval Systems -- Benchmarking for Content-Based Visual Information Search -- Posters -- Video Content Representation Based on Texture and Lighting -- Shape Similarity Measures, Properties and Constructions -- Leaf Image Retrieval with Shape Features -- A Software Framework for Combining Iconic and Semantic Content for Retrieval of Histological Images -- A Ground-Truth Training Set for Hierarchical Clustering in Content-based Image Retrieval -- Query Models and Languages for Geographical Information Systems -- Content-Based Image Retrieval By Relevance Feedback -- Chinese Cursive Script Character Image Retrieval Based on an Integrated Probability Function. | |
520 | _aPresently, in our world, visual information dominates. The turn of the millenium marks the age of visual information systems. Enabled by picture sensors of all kinds turning digital, visual information will not only enhance the value of existing information, it will also open up a new horizon of previously untapped information sources. There is a huge demand for visual information access from the consumer. As well, the handling of visual information is boosted by the rapid increase of hardware and Internet capabilities. Advanced technology for visual information systems is more urgently needed than ever before: not only new computational methods to retrieve, index, compress and uncover pictorial information, but also new metaphors to organize user interfaces. Also, new ideas and algorithms are needed which allow access to very large databases of digital pictures and videos. Finally we should not forget new systems with visual interfaces integrating the above components into new types of image, video or multimedia databases and hyperdocuments. All of these technologies will enable the construction of systems that are radically different from conventional information systems. Many novel issues will need to be addressed: query formulation for pictorial information, consistency management thereof, indexing and assessing the quality of these systems. Historically, the expression Visual Information Systems can be understood either as a system for image information or as visual system for any kind information. | ||
650 | 0 | _aComputer networks . | |
650 | 0 | _aPattern recognition systems. | |
650 | 0 | _aComputer vision. | |
650 | 0 | _aComputer graphics. | |
650 | 0 | _aNatural language processing (Computer science). | |
650 | 1 | 4 | _aComputer Communication Networks. |
650 | 2 | 4 | _aAutomated Pattern Recognition. |
650 | 2 | 4 | _aComputer Vision. |
650 | 2 | 4 | _aComputer Graphics. |
650 | 2 | 4 | _aNatural Language Processing (NLP). |
700 | 1 |
_aLaurini, Robert. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783540411772 |
776 | 0 | 8 |
_iPrinted edition: _z9783662206300 |
830 | 0 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v1929 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-40053-2 |
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