Front cover image for Image and video retrieval : 4th international conference, CIVR 2005, Singapore, and, July 20-22, 2005 : proceedings

Image and video retrieval : 4th international conference, CIVR 2005, Singapore, and, July 20-22, 2005 : proceedings

It was our great pleasure to host the 4th International Conference on Image and Video Retrieval (CIVR) at the National University of Singapore on 20–22 July 2005. In addition to the accepted submitted papers, the program also included 4 invited papers, 1 keynote industrial paper, and 4 invited industrial papers.
Print Book, English, 2005
Springer, Berlin, 2005
Kongress Singapur 2005
xvii, 672 pages : illustrations ; 24 cm
9783540278580, 9783540316787, 3540278583, 3540316787
61301850
Invited Presentations.- Lessons for the Future from a Decade of Informedia Video Analysis Research.- Large Scale Evaluations of Multimedia Information Retrieval: The TRECVid Experience.- Image and Video Retrieval from a User-Centered Mobile Multimedia Perspective.- Multimedia Research Challenges for Industry.- Industrial Presentations.- Practical Applications of Multimedia Search.- Video Story Segmentation and Its Application to Personal Video Recorders.- High-Speed Dialog Detection for Automatic Segmentation of Recorded TV Program.- Intellectual Property Management & Protection and Digital Right Management in MPEG.- Towards Media Semantics: An I2R Perspective.- Video Retrieval Techniques.- A Comparison of Score, Rank and Probability-Based Fusion Methods for Video Shot Retrieval.- EMD-Based Video Clip Retrieval by Many-to-Many Matching.- Video Story Segmentation and Event Detection.- Visual Cue Cluster Construction via Information Bottleneck Principle and Kernel Density Estimation.- Story Segmentation in News Videos Using Visual and Text Cues.- Boundary Error Analysis and Categorization in the TRECVID News Story Segmentation Task.- Semantic Event Detection in Structured Video Using Hybrid HMM/SVM.- Semantics in Video Retrieval.- What Can Expressive Semantics Tell: Retrieval Model for a Flash-Movie Search Engine.- The Use and Utility of High-Level Semantic Features in Video Retrieval.- Image Indexing and Retrieval.- Efficient Shape Indexing Using an Information Theoretic Representation.- Efficient Compressed Domain Target Image Search and Retrieval.- An Effective Multi-dimensional Index Strategy for Cluster Architectures.- Image/Video Annotation and Clustering.- Systematic Evaluation of Machine Translation Methods for Image and Video Annotation.- Automatic Image SemanticAnnotation Based on Image-Keyword Document Model.- Region-Based Image Clustering and Retrieval Using Multiple Instance Learning.- Interactive Video Retrieval and Others.- Interactive Video Search Using Multilevel Indexing.- Assessing Effectiveness in Video Retrieval.- Image/Video Retrieval Applications.- Person Spotting: Video Shot Retrieval for Face Sets.- Robust Methods and Representations for Soccer Player Tracking and Collision Resolution.- Modeling Multi-object Spatial Relationships for Satellite Image Database Indexing and Retrieval.- Video Processing, Retrieval and Multimedia Systems (Poster).- Hot Event Detection and Summarization by Graph Modeling and Matching.- Domain Knowledge Ontology Building for Semantic Video Event Description.- An Effective News Anchorperson Shot Detection Method Based on Adaptive Audio/Visual Model Generation.- Dialogue Sequence Detection in Movies.- Person Tracking and Multicamera Video Retrieval Using Floor Sensors in a Ubiquitous Environment.- Style Similarity Measure for Video Documents Comparison.- An Invariant Representation for Matching Trajectories Across Uncalibrated Video Streams.- Cyclic Sequence Comparison Using Dynamic Warping.- Design and Implementation of a Bandwidth Sensitive Distributed Continuous Media File System Using the Fibre Channel Network.- Advanced Documents Authoring Tool.- A Complete Keypics Experiment with Size Functions.- Using Projective Invariant Properties for Efficient 3D Reconstruction.- Web-Based Hybrid Visualization of Medical Images.- Similarity-Based Retrieval Method for Fractal Coded Images in the Compressed Data Domain.- A Robust Image Enhancement Technique for Improving Image Visual Quality in Shadowed Scenes.- Recycling Using Content-Based Image Retrieval on Mobile Device.- Trading Precision for Speed: Localised Similarity Functions.- Content-Based Object Movie Retrieval by Use of Relevance Feedback.- Towards Automatic Classification of 3-D Museum Artifacts Using Ontological Concepts.- Chi-Square Goodness-of-Fit Test of 3D Point Correspondence for Model Similarity Measure and Analysis.- Image Feature Extraction, Indexing and Retrieval (Poster).- Edge-Based Spatial Descriptor for Content-Based Image Retrieval.- Distributional Distances in Color Image Retrieval with GMVQ-Generated Histograms.- A Novel Texture Descriptor Using Over-Complete Wavelet Transform and Its Fractal Signature.- Region Filtering Using Color and Texture Features for Image Retrieval.- Automatic Annotation of Images from the Practitioner Perspective.- Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation.- Semantic Annotation of Image Groups with Self-organizing Maps.- A Conceptual Image Retrieval Architecture Combining Keyword-Based Querying with Transparent and Penetrable Query-by-Example.- On Image Retrieval Using Salient Regions with Vector-Spaces and Latent Semantics.- Natural / Man-Made Object Classification Based on Gabor Characteristics.- Image Object Recognition by SVMs and Evidence Theory.- Improvement on PCA and 2DPCA Algorithms for Face Recognition.- Person Search Made Easy.- Learning Shapes for Image Classification and Retrieval.- A Heuristic Search for Relevant Images on the Web.- Image Browsing: Semantic Analysis of NN k Networks.- Automated Liver Detection in Ultrasound Images.- A Weakly Supervised Approach for Semantic Image Indexing and Retrieval.- Aspect-Based Relevance Learning for Image Retrieval.- Content-Free Image Retrieval by Combinations of Keywords and User Feedbacks.- Improved AdaBoost-Based Image Retrieval with Relevance Feedback via Paired Feature Learning.
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