图象与视频检索
2006-12
湖北辞书出版社
Sundaram, Hari; Naphade, Milind; Smith, John
547
This book constitutes the refereed proceedings of the 5th International Conference on Image and Video Retrieval, CIVR 2006, held in Singapore in July 2006. The 18 revised full papers and 30 poster papers presented together with the extended abstracts of 5 papers of 1 special session and those of 10 demonstration papers were carefully reviewed and selected for inclusion in the book. Besides the invited and industrial presentations the papers are organized in topical sections on interactive image and video retrieval, semantic image retrieval, visual feature analysis, learning and classification, image and video retrieval metrics, and machine tagging.
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 TasksSession 02: 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 ExampleSession 03: 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 SequencesSession 04: 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 RetrievalSession 05: 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 WeightingSession 06: Machine Tagging Annotating News Video with Locations Automatic Person Annotation of Family Photo Album Finding People Frequently Appearing in NewsSession P1: Poster Ⅰ A Novel Framework for Robust Annotation and Retrieval in Video Sequences ……Session P2：Poster ⅡSession A：ASU Special SessionSession D：Demo SessionInvited TalksAuthor Index
