Sundaram H., Naphade M., Rui Y. (eds.) Image and Video Retrieval

Springer, 2006. — 554 p.Proceedings of 5th International Conference, CIVR 2006, Tempe, AZ, USA, July 13-15, 2006This volume contains the proceeding of the 5th International Conference on Image and Video Retrieval (CIVR), July 13–15, 2006, Arizona State University, Tempe, AZ, USA: http://www.civr2006.org. Image and video retrieval continues to be one of the most exciting and fast-growing research areas in the field of multimedia technology. However, opportunities for exchanging ideas between researchers and users of image and video retrieval systems are still limited. The International Conference on Image and Video Retrieval (CIVR) has taken on the mission of bringing together these communities to allow researchers and practitioners around the world to share points of view on image and video retrieval. A unique feature of the conference is the emphasis on participation from practitioners.
The objective is to illuminate critical issues and energize both communities for the continuing exploration of novel directions for image and video retrieval. We received over 90 submissions for the conference. Each paper was carefully reviewed by three members of the program committee, and then checked by one of the program chairs and/or general chairs. The program committee consisted of more than 40 experts in image and video retrieval from Europe, Asia and North America, and we drew upon approximately 300 high-quality reviews to ensure a thorough and fair review process. The paper submission and review process was fully electronic, using the EDAS system.
The quality of the submitted papers was very high, forcing the committee members to make some difficult decisions. Due to time and space constraints, we could only accept 18 oral papers and 30 poster papers. These 48 papers formed interesting sessions on Interactive Image and Video Retrieval, Semantic Image Retrieval, Visual Feature Analysis, Learning and Classification, Image and Video Retrieval Metrics, and Machine Tagging. To encourage participation from practitioners, we also had a strong demo session, consisting of 10 demos, ranging from VideoSOM, a SOM-based interface for video browsing, to collaborative concept tagging for images based on ontological thinking. Arizona State University (ASU) was the host of the conference, and has a very strong multimedia analysis and retrieval program. We therefore also included a special ASU session of 5 papers.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
Finding Faces 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: Hierarchical Synthetic Image Classification Using Image Searchand 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