Media Streams: an iconic visual language for video representation
Human-computer interaction
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tools for Browsing a TV Situation Comedy Based on Content Specific Attributes
Multimedia Tools and Applications
Filter Image Browsing: Interactive Image Retrieval by Using Database Overviews
Multimedia Tools and Applications
Composition and Search with a Video Algebra
IEEE MultiMedia
Name-It: Naming and Detecting Faces in News Videos
IEEE MultiMedia
Everything You Wanted to Know About MPEG-7: Part 1
IEEE MultiMedia
Cinematic Primitives for Multimedia
IEEE Computer Graphics and Applications
Learning to Recognize Speech by Watching Television
IEEE Intelligent Systems
Multimodal Person Identification in Movies
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
A System for Effortless Content Annotation to Unfold the Semantics in Videos
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Systematic evaluation of logical story unit segmentation
IEEE Transactions on Multimedia
Action movies segmentation and summarization based on tempo analysis
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Components and systems for interactive video indexing
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Modeling multimedia data semantics with MADS
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
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Effectively labeling the visual content of movies is essential for annotation. We present the interactive and adaptive i-Notation system, which describes actors' names, automatically processes multimodal information sources, and deals with available sources' varying quality. It provides the basis for intelligent interaction and demonstrates significant improvements in annotation efficiency.