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Image and Video Retrieval

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Cover of 'Image and Video Retrieval'

Table of Contents

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    Book Overview
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    Chapter 1 Interactive Experiments in Object-Based Retrieval
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    Chapter 2 Learned Lexicon-Driven Interactive Video Retrieval
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    Chapter 3 Mining Novice User Activity with TRECVID Interactive Retrieval Tasks
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    Chapter 4 A Linear-Algebraic Technique with an Application in Semantic Image Retrieval
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    Chapter 5 Logistic Regression of Generic Codebooks for Semantic Image Retrieval
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    Chapter 6 Query by Semantic Example
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    Chapter 7 Corner Detectors for Affine Invariant Salient Regions: Is Color Important?
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    Chapter 8 Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help?
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    Chapter 9 Local Feature Trajectories for Efficient Event-Based Indexing of Video Sequences
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    Chapter 10 A Cascade of Unsupervised and Supervised Neural Networks for Natural Image Classification
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    Chapter 11 Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
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    Chapter 12 Efficient Margin-Based Rank Learning Algorithms for Information Retrieval
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    Chapter 13 Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
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    Chapter 14 Video Clip Matching Using MPEG-7 Descriptors and Edit Distance
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    Chapter 15 Video Retrieval Using High Level Features: Exploiting Query Matching and Confidence-Based Weighting
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    Chapter 16 Annotating News Video with Locations
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    Chapter 17 Automatic Person Annotation of Family Photo Album
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    Chapter 18 Finding People Frequently Appearing in News
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    Chapter 19 A Novel Framework for Robust Annotation and Retrieval in Video Sequences
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    Chapter 20 Feature Re-weighting in Content-Based Image Retrieval
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    Chapter 21 Objectionable Image Detection by ASSOM Competition
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    Chapter 22 Image Searching and Browsing by Active Aspect-Based Relevance Learning
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    Chapter 23 Finding Faces in Gray Scale Images Using Locally Linear Embeddings
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    Chapter 24 ROI-Based Medical Image Retrieval Using Human-Perception and MPEG-7 Visual Descriptors
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    Chapter 25 Hierarchical Hidden Markov Model for Rushes Structuring and Indexing
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    Chapter 26 Retrieving Objects Using Local Integral Invariants
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    Chapter 27 Retrieving Shapes Efficiently by a Qualitative Shape Descriptor: The Scope Histogram
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    Chapter 28 Relay Boost Fusion for Learning Rare Concepts in Multimedia
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    Chapter 29 Comparison Between Motion Verbs Using Similarity Measure for the Semantic Representation of Moving Object
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    Chapter 30 Coarse-to-Fine Classification for Image-Based Face Detection
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    Chapter 31 Using Topic Concepts for Semantic Video Shots Classification
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    Chapter 32 A Multi-feature Optimization Approach to Object-Based Image Classification
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    Chapter 33 Eliciting Perceptual Ground Truth for Image Segmentation
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    Chapter 34 Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval
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    Chapter 35 Video Navigation Based on Self-Organizing Maps
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    Chapter 36 Fuzzy SVM Ensembles for Relevance Feedback in Image Retrieval
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    Chapter 37 Video Mining with Frequent Itemset Configurations
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    Chapter 38 Using High-Level Semantic Features in Video Retrieval
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    Chapter 39 Recognizing Objects and Scenes in News Videos
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    Chapter 40 Face Retrieval in Broadcasting News Video by Fusing Temporal and Intensity Information
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    Chapter 41 Multidimensional Descriptor Indexing: Exploring the BitMatrix
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    Chapter 42 Natural Scene Image Modeling Using Color and Texture Visterms
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    Chapter 43 Online Image Retrieval System Using Long Term Relevance Feedback
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    Chapter 44 Perceptual Distance Functions for Similarity Retrieval of Medical Images
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    Chapter 45 Using Score Distribution Models to Select the Kernel Type for a Web-Based Adaptive Image Retrieval System (AIRS)
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    Chapter 46 Semantics Supervised Cluster-Based Index for Video Databases
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    Chapter 47 Semi-supervised Learning for Image Annotation Based on Conditional Random Fields
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    Chapter 48 NPIC: Hierarchical Synthetic Image Classification Using Image Search and Generic Features
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    Chapter 49 Context-Aware Media Retrieval
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    Chapter 50 Estimating the Physical Effort of Human Poses
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    Chapter 51 Modular Design of Media Retrieval Workflows Using ARIA
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    Chapter 52 Image Rectification for Stereoscopic Visualization Without 3D Glasses
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    Chapter 53 Human Movement Analysis for Interactive Dance
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    Chapter 54 Exploring the Dynamics of Visual Events in the Multi-dimensional Semantic Concept Space
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    Chapter 55 VideoSOM: A SOM-Based Interface for Video Browsing
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    Chapter 56 iBase: Navigating Digital Library Collections
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    Chapter 57 Exploring the Synergy of Humans and Machines in Extreme Video Retrieval
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    Chapter 58 Efficient Summarizing of Multimedia Archives Using Cluster Labeling
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    Chapter 59 Collaborative Concept Tagging for Images Based on Ontological Thinking
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    Chapter 60 Multimodal Search for Effective Video Retrieval
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    Chapter 61 MediAssist: Using Content-Based Analysis and Context to Manage Personal Photo Collections
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    Chapter 62 Mediamill: Advanced Browsing in News Video Archives
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    Chapter 63 A Large Scale System for Searching and Browsing Images from the World Wide Web
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    Chapter 64 Embrace and Tame the Digital Content
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    Chapter 65 Discovering a Fish in a Forest of Trees – False Positives and User Expectations in Visual Retrieval: Experiments in CBIR and the Visual Arts
Overall attention for this book and its chapters
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Title
Image and Video Retrieval
Published by
Springer Berlin Heidelberg, June 2006
DOI 10.1007/11788034
ISBNs
978-3-54-036018-6, 978-3-54-036019-3
Editors

Sundaram, Hari, Naphade, Milind, Smith, John R., Rui, Yong

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 3%
Student > Bachelor 1 1%
Unknown 64 96%
Readers by discipline Count As %
Engineering 2 3%
Economics, Econometrics and Finance 1 1%
Unknown 64 96%