ImageCLEF Experimental Evaluation in Visual Information Retrieval 1st Edition by Henning Muller, Paul Clough, Thomas Deselaers, Barbara Caputo ISBN 3642151817 9783642151811

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ISBN 10: 3642151817
ISBN 13: 9783642151811
Author: Henning Muller, Paul Clough, Thomas Deselaers, Barbara Caputo

The pervasive creation and consumption of content, especially visual content, is ingrained into our modern world. We’re constantly consuming visual media content, in printed form and in digital form, in work and in leisure pursuits. Like our cave– man forefathers, we use pictures to record things which are of importance to us as memory cues for the future, but nowadays we also use pictures and images to document processes; we use them in engineering, in art, in science, in medicine, in entertainment and we also use images in advertising. Moreover, when images are in digital format, either scanned from an analogue format or more often than not born digital, we can use the power of our computing and networking to exploit images to great effect. Most of the technical problems associated with creating, compressing, storing, transmitting, rendering and protecting image data are already solved. We use – cepted standards and have tremendous infrastructure and the only outstanding ch- lenges, apart from managing the scale issues associated with growth, are to do with locating images. That involves analysing them to determine their content, clas- fying them into related groupings, and searching for images. To overcome these challenges we currently rely on image metadata, the description of the images, – ther captured automatically at creation time or manually added afterwards.

ImageCLEF Experimental Evaluation in Visual Information Retrieval 1st Table of contents:

Seven Years of Image Retrieval Evaluation
Introduction
Evaluation of IR Systems
IR Test Collections
Cross–Language Evaluation Forum (CLEF)
ImageCLEF
Aim and Objectives
Tasks and Participants
Data sets
Contributions
Organisational Challenges
Conclusions
References
Data Sets Created in ImageCLEF
Introduction
Collection Creation
Requirements and Specification
Collection Overview
Image Collections for Photographic Retrieval
The St. Andrews Collection of Historic Photographs
The IAPR TC–12 Database
The Belga News Agency Photographic Collection
Image Collections for Medical Retrieval
The ImageCLEFmed Teaching Files
The RSNA Database
Automatic Image Annotation and Object Recognition
The IRMA Database
The LookThatUp (LTU) Data set
The PASCAL Object Recognition Database
The MIR Flickr Image Data Set
Image Collections in Other Tasks
The INEX MM Wikipedia Collection
The KTH–IDOL2 Database
Conclusions
References
Creating Realistic Topics for Image Retrieval Evaluation
Introduction
User Models and Information Sources
Machine–Oriented Evaluation
User Models
Information Sources for Topic Creation
Concrete Examples for Generated Visual Topics in Several Domains
Photographic Retrieval
Medical Retrieval
The Influence of Topics on the Results of Evaluation
Classifying Topics Into Categories
Links Between Topics and the Relevance Judgments
What Can Be Evaluated and What Can Not?
Conclusions
References
Relevance Judgments for Image Retrieval Evaluation
Introduction
Overview of Relevance Judgments in Information Retrieval
Test Collections
Relevance Judgments
Relevance Judging for the ImageCLEF Medical Retrieval Task
Topics and Collection
Judges
Relevance Judgment Systems and the Process of Judging
Conclusions and Future Work
References
Performance Measures Used in Image Information Retrieval
Evaluation Measures Used in ImageCLEF
Measures for Retrieval
Measuring at Fixed Recall
Measuring at Fixed Rank
Measures for Diversity
Collating Two Measures Into One
Miscellaneous Measures
Considering Multiple Measures
Measures for Image Annotation and Concept Detection
Use of Measures in ImageCLEF
Conclusions
References
Fusion Techniques for Combining Textual and Visual Information Retrieval
Introduction
Information Fusion and Orthogonality
Methods
Results
Early Fusion Approaches
Late Fusion Approaches
Inter–media Feedback with Query Expansion
Other Approaches
Overview of the Methods from 2004–2009
Justification for the Approaches and Generally Known Problems
Conclusions
References
Track Reports
Interactive Image Retrieval
Interactive Studies in Information Retrieval
iCLEF Experiments on Interactive Image Retrieval
iCLEF Image Retrieval Experiments: The Latin Square Phase
iCLEF Experiments with Flickr
The Target Collection: Flickr
Annotations
The Task
Experiments
Task Space, Technology and Research Questions
Use Cases for Interactive Image Retrieval
Challenges: Technology and Interaction
References
Photographic Image Retrieval
Introduction
Ad hoc Retrieval of Historic Photographs: ImageCLEF 2003–2005
Test Collection and Distribution
Query Topics
Relevance Judgments and Performance Measures
Results and Analysis
Ad hoc Retrieval of Generic Photographs: ImageCLEFphoto 2006-2007
Test Collection and Distribution
Query Topics
Relevance Judgments and Performance Measures
Results and Analysis
Visual Sub–task
Ad hoc Retrieval and Result Diversity: ImageCLEFphoto 2008–2009
Test Collection and Distribution
Query Topics
Relevance Judgments and Performance Measures
Results and Analysis
Conclusion and Future Prospects
References
The Wikipedia Image Retrieval Task
Introduction
Task Overview
Evaluation Objectives
Wikipedia Image Collection
Additional Resources
Topics
Relevance Assessments
Evaluation
Participants
Approaches
Results
Discussion
Best Practices
Open Issues
Conclusions and the Future of the Task
References
The Robot Vision Task
Introduction
The Robot Vision Task at ImageCLEF 2009: Objectives and Overview
The Robot Vision Task 2009
Robot Vision 2009: The Database
Robot Vision 2009: Performance Evaluation
Robot Vision 2009: Approaches and Results
Moving Forward: Robot Vision in 2010
The Robot Vision Task at ICPR2010
The Robot Vision Task at ImageCLEF2010
Conclusions
References
Object and Concept Recognition for Image Retrieval
Introduction
History of the ImageCLEF Object and Concept Recognition Tasks
2006: Object Annotation Task
2007: Object Retrieval Task
2008: Visual Concept Detection Task
2009: Visual Concept Detection Task
Approaches to Object Recognition
Descriptors
Feature Post–processing and Codebook Generation
Classifier
Post–Processing
Results
2006: Object Annotation Task
2007: Object Retrieval Task
2008: Visual Concept Detection Task
2009: Visual Concept Detection Task
Evolution of Concept Detection Performance
Discussion
Combinations with the Photo Retrieval Task
Conclusion
References
The Medical Image Classification Task
Introduction
History of ImageCLEF Medical Annotation
The Aim of the Challenge
The Database
Error Evaluation
Approaches to Medical Image Annotation
Image Representation
Classification Methods
Hierarchy
Unbalanced Class Distribution
Results
Conclusion
References
The Medical Image Retrieval Task
Introduction
Participation in the Medical Retrieval Task
Development of Databases and Tasks over the Years
2004
2005–2007
2008–2009
Evolution of Techniques Used by the Participants
Visual Retrieval
Textual Retrieval
Combining Visual and Textual Retrieval
Case–Based Retrieval Topics
Results
Visual Retrieval
Textual Retrieval
Mixed Retrieval
Relevance Feedback and Manual Query Reformulation
Main Lessons Learned
Conclusions
References
Participant reports
Expansion and Re–ranking Approaches for Multimodal Image Retrieval using Text–based Methods
Introduction
Integrated Retrieval Model
Handling Multi–modality in the Vector Space Model
Document and Query Expansion
Re–ranking
Level 1: Narrowing-down and Re-indexing
Level 2: Cover Coefficient Based Re–ranking
Results
Conclusions
References
Revisiting Sub–topic Retrieval in the ImageCLEF 2009 Photo Retrieval Task
Introduction
Background and Related Work
Sub–topic Retrieval
The Probability Ranking Principle
Beyond Independent Relevance
Document Clustering and Inter–Cluster Document Selection
Re–examining Document Clustering Techniques
Clustering for Sub–topic Retrieval
Empirical Study
Results
Conclusions
References
Knowledge Integration using Textual Information for Improving ImageCLEF Collections
Introduction
System Description
Photo Retrieval System
Medical Retrieval System
Photo Task
Using Several IR and a Voting System
Filtering
Clustering
The Medical Task
Metadata Selection using Information Gain
Expanding with Ontologies
Fusion of Visual and Textual Lists
Conclusion and Further Work
References
Leveraging Image, Text and Cross–media Similarities for Diversity–focused Multimedia Retrieval
Introduction
Content–Based Image Retrieval
Fisher Vector Representation of Images
Image Retrieval at ImageCLEF Photo
Text Representation and Retrieval
Language Models
Text Enrichment at ImageCLEF Photo
Text–Image Information Fusion
Cross–Media Similarities
Cross–Media Retrieval at ImageCLEF Photo
Diversity–focused Multimedia Retrieval
Re–ranking Top–Listed Documents to Promote Diversity
Diversity–focused Retrieval at ImageCLEF Photo
Conclusion
References
University of Amsterdam at the Visual Concept Detection and Annotation Tasks
Introduction
Concept Detection Pipeline
Point Sampling Strategy
Color Descriptor Extraction
Bag–of–Words model
Machine Learning
Experiments
Spatial Pyramid Levels
Point Sampling Strategies and Color Descriptors
Combinations of Sampling Strategies and Descriptors
Discussion
ImageCLEF 2009
Evaluation Per Image
Conclusion
ImageCLEF@ICPR 2010
Conclusion
References
Intermedia Conceptual Indexing
Introduction
Conceptual Indexing
Concept Usage and Definition in IR
Concept Mapping to Text
Mapping Steps
IR Models Using Concepts
Experiments using the ImageCLEF Collection
Image Indexing using a Visual Ontology
Image Indexing Based on VisMed Terms
FlexiTile Matching
Medical Image Retrieval Using VisMed Terms
Spatial Visual Queries
Multimedia and Intermedia Indexing
Conclusions
References
Conceptual Indexing Contribution to ImageCLEF Medical Retrieval Tasks
Introduction
Semantic Indexing Using Ontologies
Conceptual Indexing
Language Models for Concepts
Concept Detection
Concept Evaluation Using ImageCLEFmed 2005–07
From Concepts to Graphs
A Language Model for Graphs
Graph Detection
Graph Results on ImageCLEFmed 2005–07
Mixing Concept Sources
Query Fusion
Document Model Fusion
Joint Decomposition
Results on ImageCLEFmed 2005–07
Adding Pseudo–Feedback
Pseudo–Relevance Feedback Model
Results
Conclusions
References
Improving Early Precision in the ImageCLEF Medical Retrieval Task
Introduction
What is Early Precision?
Why Improve Early Precision?
ImageCLEF
Our System
User Interface
Image Database
Query Parsing and Indexing
Improving Precision
Modality Filtration
Using Modality Information for Retrieval
Using Interactive Retrieval
Conclusions
References
Lung Nodule Detection
Introduction
Lung Cancer — Clinical Motivation
Computer–Aided Detection of Lung Nodules
Ground Truth for Lesions
Review of Existing Techniques
Gray–Level Threshold
Template Matching
Spherical Enhancing Filters
Description of Siemens LungCAD System
Lung Segmentation
Candidate Generation
Feature Extraction
Classification
Multiple Instance Learning
Exploiting Domain Knowledge in Data–Driven Training–Gated Classifiers
Ground Truth Creation: Learning from Multiple Experts
ImageCLEF Challenge
Materials and Methods
Results
Discussion and Conclusions
Clinical Impact
Future Extensions of CAD
References
Medical Image Classification at Tel Aviv and Bar Ilan Universities
Introduction
Visual Words in Medical Archives
The Proposed TAU–BIU Classification System Based on a Dictionary of Visual–Words
Patch Extraction
Feature Space Description
Quantization
From an Input Image to a Representative Histogram
Classification
Experiments and Results
Sensitivity Analysis
Optimizing the Classifier
Classification Results
Discussion
References
Idiap on Medical Image Classification
Introduction
Multiple Cues for Image Annotation
High–Level Integration
Mid–Level Integration
Low–Level Integration
Exploiting the Hierarchical Structure of Data: Confidence Based Opinion Fusion
Facing the Class Imbalance Problem: Virtual Examples
Experiments
Features
Classifier
Experimental Set–up and Results
Conclusions
References
External views
Press Association Images — Image Retrieval Challenges
Press Association Images — A Brief History
The Press Association
Images at the Press Association
User Search Behaviour
Types of Users
Types of Search
Challenges
Semantic Web for Multimedia Applications
Introduction to the Semantic Web
Success Stories and Research Areas
The Semantic Web Project at Press Association Images
Utilizing Semantic Web Technologies for Improving User Experience in Image Browsing
PA Data set: Linking to the Linked Data Cloud
Information Extraction and Semantic Annotation
Conclusions and Future Work
References
Image Retrieval in a Commercial Setting
Introduction
Evaluating Large Scale Image Search Systems
Query Logs and Click Data
Background Information on Image Search
Multilayer Perceptron
Click Data
Data Representation
Textual Features
Visual Features
Evaluation and Results
Analysis of Features
Discussion of Results
Looking Ahead
References
An Overview of Evaluation Campaigns in Multimedia Retrieval
Introduction
ImageCLEF in Multimedia IR (MIR)
INEX XML Multimedia Track
MIREX
GeoCLEF
TRECVid
VideOlympics
PASCAL Visual Object Classes (VOC) Challenge
MediaEval and VideoCLEF
Past Benchmarking Evaluation Campaigns
Comparison with ImageCLEF
Utility of Evaluation Conferences
Impact and Evolution of Metrics

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