000 | 06137nam a22006495i 4500 | ||
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001 | 978-3-540-45925-5 | ||
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008 | 121227s2002 gw | s |||| 0|eng d | ||
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_a9783540459255 _9978-3-540-45925-5 |
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024 | 7 |
_a10.1007/3-540-45925-1 _2doi |
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_aUYQV _2bicssc |
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_aCOM016000 _2bisacsh |
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_a006.37 _223 |
245 | 1 | 0 |
_aRecent Advances in Visual Information Systems _h[electronic resource] : _b5th International Conference, VISUAL 2002 Hsin Chu, Taiwan, March 11-13, 2002. Proceedings / _cedited by Shi-Kuo Chang, Zen Chen, Suh-Yin Lee. |
250 | _a1st ed. 2002. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2002. |
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300 |
_aXII, 328 p. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2314 |
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505 | 0 | _aInvited Talk -- Multi-sensor Information Fusion by Query Refinement -- Content-Based Indexing, Search and Retrieval -- MiCRoM: A Metric Distance to Compare Segmented Images -- Image Retrieval by Regions: Coarse Segmentation and Fine Color Description -- Fast Approximate Nearest-Neighbor Queries in Metric Feature Spaces by Buoy Indexing -- A Binary Color Vision Framework for Content-Based Image Indexing -- Region-Based Image Retrieval Using Multiple-Features -- A Bayesian Method for Content-Based Image Retrieval by Use of Relevance Feedback -- Color Image Retrieval Based on Primitives of Color Moments -- Invariant Feature Extraction and Object Shape Matching Using Gabor Filtering -- Visual Information System Architectures -- A Framework for Visual Information Retrieval -- Feature Extraction and a Database Strategy for Video Fingerprinting -- ImageGrouper: Search, Annotate and Organize Images by Groups -- Toward a Personalized CBIR System -- Image/Video Databases -- An Efficient Storage Organization for Multimedia Databases -- Unsupervised Categorization for Image Database Overview -- A Data-Flow Approach to Visual Querying in Large Spatial Databases -- MEDIMAGE - A Multimedia Database Management System for Alzheimer’s Disease Patients -- Networked Video -- Life after Video Coding Standards: Rate Shaping and Error Concealment -- A DCT-Domain Video Transcoder for Spatial Resolution Downconversion -- A Receiver-Driven Channel Adjustment Scheme for Periodic Broadcast of Streaming Video -- Video Object Hyper-Links for Streaming Applications -- Application Areas of Visual Information Systems -- Scalable Hierarchical Summarization of News Using Fidelity in MPEG-7 Description Scheme -- MPEG-7 Descriptors in Content-Based Image Retrieval with PicSOM System -- Fast Text Caption Localization on Video UsingVisual Rhythm -- A New Digital Watermarking Technique for Video -- Automatic Closed Caption Detection and Font Size Differentiation in MPEG Video -- Motion Activity Based Shot Identification and Closed Caption Detection for Video Structuring -- Visualizing the Construction of Generic Bills of Material -- Data and Knowledge Visualization in Knowledge Discovery Process. | |
520 | _aVisualinformationsystemsareinformationsystemsforvisualcomputing.Visual computing is computing on visual objects. Some visual objects such as images are inherently visual in the sense that their primary representation is the visual representation.Somevisualobjectssuchasdatastructuresarederivativelyvisual in the sense that their primary representation is not the visual representation, but can be transformed into a visual representation. Images and data structures are the two extremes. Other visual objects such as maps may fall somewhere in between the two. Visual computing often involves the transformation from one type of visual objects into another type of visual objects, or into the same type of visual objects, to accomplish certain objectives such as information reduction, object recognition, and so on. In visual information systems design it is also important to ask the foll- ing question: who performs the visual computing? The answer to this question determines the approach to visual computing. For instance it is possible that primarily the computer performs the visual computing and the human merely observes the results. It is also possible that primarily the human performs the visual computing and the computer plays a supporting role. Often the human and the computer are both involved as equal partners in visual computing and there are visual interactions. Formal or informal visual languages are usually needed to facilitate such visual interactions. | ||
650 | 0 | _aComputer vision. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 | _aApplication software. | |
650 | 0 | _aDatabase management. | |
650 | 0 | _aComputer graphics. | |
650 | 0 | _aNatural language processing (Computer science). | |
650 | 1 | 4 | _aComputer Vision. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aComputer and Information Systems Applications. |
650 | 2 | 4 | _aDatabase Management. |
650 | 2 | 4 | _aComputer Graphics. |
650 | 2 | 4 | _aNatural Language Processing (NLP). |
700 | 1 |
_aChang, Shi-Kuo. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aChen, Zen. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aLee, Suh-Yin. _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: _z9783540433583 |
776 | 0 | 8 |
_iPrinted edition: _z9783662207482 |
830 | 0 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2314 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-45925-1 |
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912 | _aZDB-2-SXCS | ||
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942 | _cSPRINGER | ||
999 |
_c188027 _d188027 |