Image and Video Retrieval
-15%
portes grátis
Image and Video Retrieval
5th Internatinoal Conference, CIVR 2006, Tempe, AZ, USA, July 13-15, 2006, Proceedings
Sundaram, Hari; Rui, Yong; Naphade, Milind; Smith, John
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
06/2006
548
Mole
Inglês
9783540360186
15 a 20 dias
1730
Descrição não disponível.
Session O1: Interactive Image and Video Retrieval.- Interactive Experiments in Object-Based Retrieval.- Learned Lexicon-Driven Interactive Video Retrieval.- Mining Novice User Activity with TRECVID Interactive Retrieval Tasks.- Session O2: Semantic Image Retrieval.- A Linear-Algebraic Technique with an Application in Semantic Image Retrieval.- Logistic Regression of Generic Codebooks for Semantic Image Retrieval.- Query by Semantic Example.- Session O3: Visual Feature Analysis.- Corner Detectors for Affine Invariant Salient Regions: Is Color Important?.- Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help?.- Local Feature Trajectories for Efficient Event-Based Indexing of Video Sequences.- Session O4: Learning and Classification.- A Cascade of Unsupervised and Supervised Neural Networks for Natural Image Classification.- Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation.- Efficient Margin-Based Rank Learning Algorithms for Information Retrieval.- Session O5: Image and Video Retrieval Metrics.- Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure.- Video Clip Matching Using MPEG-7 Descriptors and Edit Distance.- Video Retrieval Using High Level Features: Exploiting Query Matching and Confidence-Based Weighting.- Session O6: Machine Tagging.- Annotating News Video with Locations.- Automatic Person Annotation of Family Photo Album.- Finding People Frequently Appearing in News.- Session P1: Poster I.- A Novel Framework for Robust Annotation and Retrieval in Video Sequences.- Feature Re-weighting in Content-Based Image Retrieval.- Objectionable Image Detection by ASSOM Competition.- Image Searching and Browsing by Active Aspect-Based Relevance Learning.- FindingFaces in Gray Scale Images Using Locally Linear Embeddings.- ROI-Based Medical Image Retrieval Using Human-Perception and MPEG-7 Visual Descriptors.- Hierarchical Hidden Markov Model for Rushes Structuring and Indexing.- Retrieving Objects Using Local Integral Invariants.- Retrieving Shapes Efficiently by a Qualitative Shape Descriptor: The Scope Histogram.- Relay Boost Fusion for Learning Rare Concepts in Multimedia.- Comparison Between Motion Verbs Using Similarity Measure for the Semantic Representation of Moving Object.- Coarse-to-Fine Classification for Image-Based Face Detection.- Using Topic Concepts for Semantic Video Shots Classification.- A Multi-feature Optimization Approach to Object-Based Image Classification.- Eliciting Perceptual Ground Truth for Image Segmentation.- Session P2: Poster II.- Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval.- Video Navigation Based on Self-Organizing Maps.- Fuzzy SVM Ensembles for Relevance Feedback in Image Retrieval.- Video Mining with Frequent Itemset Configurations.- Using High-Level Semantic Features in Video Retrieval.- Recognizing Objects and Scenes in News Videos.- Face Retrieval in Broadcasting News Video by Fusing Temporal and Intensity Information.- Multidimensional Descriptor Indexing: Exploring the BitMatrix.- Natural Scene Image Modeling Using Color and Texture Visterms.- Online Image Retrieval System Using Long Term Relevance Feedback.- Perceptual Distance Functions for Similarity Retrieval of Medical Images.- Using Score Distribution Models to Select the Kernel Type for a Web-Based Adaptive Image Retrieval System (AIRS).- Semantics Supervised Cluster-Based Index for Video Databases.- Semi-supervised Learning for Image Annotation Based on Conditional Random Fields.- NPIC: HierarchicalSynthetic Image Classification Using Image Search and Generic Features.- Session A: ASU Special Session.- Context-Aware Media Retrieval.- Estimating the Physical Effort of Human Poses.- Modular Design of Media Retrieval Workflows Using ARIA.- Image Rectification for Stereoscopic Visualization Without 3D Glasses.- Human Movement Analysis for Interactive Dance.- Session D: Demo Session.- Exploring the Dynamics of Visual Events in the Multi-dimensional Semantic Concept Space.- VideoSOM: A SOM-Based Interface for Video Browsing.- iBase: Navigating Digital Library Collections.- Exploring the Synergy of Humans and Machines in Extreme Video Retrieval.- Efficient Summarizing of Multimedia Archives Using Cluster Labeling.- Collaborative Concept Tagging for Images Based on Ontological Thinking.- Multimodal Search for Effective Video Retrieval.- MediAssist: Using Content-Based Analysis and Context to Manage Personal Photo Collections.- Mediamill: Advanced Browsing in News Video Archives.- A Large Scale System for Searching and Browsing Images from the World Wide Web.- Invited Talks.- Embrace and Tame the Digital Content.- Discovering a Fish in a Forest of Trees - False Positives and User Expectations in Visual Retrieval: Experiments in CBIR and the Visual Arts.
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Augmented Reality;MPEG-7;Multimedia;Stereo;computer vision;configuration;content-based image retrieval;feature-based retrieval;image databases;image retrieval;indexing;machine tagging;modeling;multimedia retrieval;visualization
Session O1: Interactive Image and Video Retrieval.- Interactive Experiments in Object-Based Retrieval.- Learned Lexicon-Driven Interactive Video Retrieval.- Mining Novice User Activity with TRECVID Interactive Retrieval Tasks.- Session O2: Semantic Image Retrieval.- A Linear-Algebraic Technique with an Application in Semantic Image Retrieval.- Logistic Regression of Generic Codebooks for Semantic Image Retrieval.- Query by Semantic Example.- Session O3: Visual Feature Analysis.- Corner Detectors for Affine Invariant Salient Regions: Is Color Important?.- Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help?.- Local Feature Trajectories for Efficient Event-Based Indexing of Video Sequences.- Session O4: Learning and Classification.- A Cascade of Unsupervised and Supervised Neural Networks for Natural Image Classification.- Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation.- Efficient Margin-Based Rank Learning Algorithms for Information Retrieval.- Session O5: Image and Video Retrieval Metrics.- Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure.- Video Clip Matching Using MPEG-7 Descriptors and Edit Distance.- Video Retrieval Using High Level Features: Exploiting Query Matching and Confidence-Based Weighting.- Session O6: Machine Tagging.- Annotating News Video with Locations.- Automatic Person Annotation of Family Photo Album.- Finding People Frequently Appearing in News.- Session P1: Poster I.- A Novel Framework for Robust Annotation and Retrieval in Video Sequences.- Feature Re-weighting in Content-Based Image Retrieval.- Objectionable Image Detection by ASSOM Competition.- Image Searching and Browsing by Active Aspect-Based Relevance Learning.- FindingFaces in Gray Scale Images Using Locally Linear Embeddings.- ROI-Based Medical Image Retrieval Using Human-Perception and MPEG-7 Visual Descriptors.- Hierarchical Hidden Markov Model for Rushes Structuring and Indexing.- Retrieving Objects Using Local Integral Invariants.- Retrieving Shapes Efficiently by a Qualitative Shape Descriptor: The Scope Histogram.- Relay Boost Fusion for Learning Rare Concepts in Multimedia.- Comparison Between Motion Verbs Using Similarity Measure for the Semantic Representation of Moving Object.- Coarse-to-Fine Classification for Image-Based Face Detection.- Using Topic Concepts for Semantic Video Shots Classification.- A Multi-feature Optimization Approach to Object-Based Image Classification.- Eliciting Perceptual Ground Truth for Image Segmentation.- Session P2: Poster II.- Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval.- Video Navigation Based on Self-Organizing Maps.- Fuzzy SVM Ensembles for Relevance Feedback in Image Retrieval.- Video Mining with Frequent Itemset Configurations.- Using High-Level Semantic Features in Video Retrieval.- Recognizing Objects and Scenes in News Videos.- Face Retrieval in Broadcasting News Video by Fusing Temporal and Intensity Information.- Multidimensional Descriptor Indexing: Exploring the BitMatrix.- Natural Scene Image Modeling Using Color and Texture Visterms.- Online Image Retrieval System Using Long Term Relevance Feedback.- Perceptual Distance Functions for Similarity Retrieval of Medical Images.- Using Score Distribution Models to Select the Kernel Type for a Web-Based Adaptive Image Retrieval System (AIRS).- Semantics Supervised Cluster-Based Index for Video Databases.- Semi-supervised Learning for Image Annotation Based on Conditional Random Fields.- NPIC: HierarchicalSynthetic Image Classification Using Image Search and Generic Features.- Session A: ASU Special Session.- Context-Aware Media Retrieval.- Estimating the Physical Effort of Human Poses.- Modular Design of Media Retrieval Workflows Using ARIA.- Image Rectification for Stereoscopic Visualization Without 3D Glasses.- Human Movement Analysis for Interactive Dance.- Session D: Demo Session.- Exploring the Dynamics of Visual Events in the Multi-dimensional Semantic Concept Space.- VideoSOM: A SOM-Based Interface for Video Browsing.- iBase: Navigating Digital Library Collections.- Exploring the Synergy of Humans and Machines in Extreme Video Retrieval.- Efficient Summarizing of Multimedia Archives Using Cluster Labeling.- Collaborative Concept Tagging for Images Based on Ontological Thinking.- Multimodal Search for Effective Video Retrieval.- MediAssist: Using Content-Based Analysis and Context to Manage Personal Photo Collections.- Mediamill: Advanced Browsing in News Video Archives.- A Large Scale System for Searching and Browsing Images from the World Wide Web.- Invited Talks.- Embrace and Tame the Digital Content.- Discovering a Fish in a Forest of Trees - False Positives and User Expectations in Visual Retrieval: Experiments in CBIR and the Visual Arts.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
