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» A two-level relevance feedback mechanism for image retrieval
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MM
2006
ACM
158views Multimedia» more  MM 2006»
15 years 3 months ago
Extreme video retrieval: joint maximization of human and computer performance
We present an efficient system for video search that maximizes the use of human bandwidth, while at the same time exploiting the machine’s ability to learn in real-time from use...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
MMM
2007
Springer
143views Multimedia» more  MMM 2007»
15 years 4 months ago
Semi-supervised Cast Indexing for Feature-Length Films
Abstract. Cast indexing is a very important application for contentbased video browsing and retrieval, since the characters in feature-length films and TV series are always the ma...
Wei Fan, Tao Wang, Jean-Yves Bouguet, Wei Hu, Yimi...
SIGECOM
2004
ACM
127views ECommerce» more  SIGECOM 2004»
15 years 3 months ago
HYRIWYG: leveraging personalization to elicit honest recommendations
This paper presents HYRIWYG (How You Rate Influences What You Get), a reputation system applicable to Internet Recommendation Systems (RS). The novelty lies in the incentive mecha...
Ana Cristina Bicharra Garcia, Martin Ekstrom, Hans...
ICCV
2007
IEEE
15 years 11 months ago
Interactive Search for Image Categories by Mental Matching
Traditional image retrieval methods require a "query image" to initiate a search for members of an image category. However, when the image database is unstructured, and ...
Marin Ferecatu, Donald Geman
CVPR
2007
IEEE
15 years 1 months ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...