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Learning / Statistical classification / Machine learning / Computer vision / AdaBoost / Support vector machine / Boosting / Feature / Boosting methods for object categorization / Artificial intelligence / Statistics / Ensemble learning


TRECVID 2007 by the Brno Group High Level Feature Extraction & Shot Boundary Detection Adam Herout, Vítězslav Beran, Michal Hradiš, Igor Potúček, Pavel Zemčík, Petr Chmelař
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Document Date: 2008-03-03 10:55:06

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Company

Brno Image Processing Group / Run Precision / Intel / /

Country

Japan / /

Currency

SBD / /

Event

Product Issues / Product Recall / /

Facility

SVM library / Brno University of Technology / /

IndustryTerm

traffic applications / car detection / faster then real-time annotation / video annotation tool / grid-search / image processing / base-line solution / on-line learning / video processing / videosequence processing / similar frame-processing engines / generic software pieces / learning algorithm / hand-annotated using a video annotation tool / /

Movie

D.3 / D.5 / D.2 / D.4 / /

Organization

Sciences Grant Agency / Faculty of Information Technology / Department of Computer Graphics and Multimedia / European Union / Brno University of Technology / Grant Agency of the Czech Republic / Czech Academy / /

Person

Igor Potúček / Adam Herout / Petr Chmelař / Pavel Zemčík / Michal Hradiš / /

Position

selected SVM model for each high level feature / Singer / quantities rt / /

Product

Precision / AdaBoost / /

PublishedMedium

Sound and Vision / Machine Learning / Computer Graphics / /

Technology

learning algorithm / Information Technology / AdaBoost learning algorithm / Machine Learning / AdaBoost algorithm / image processing / /

URL

http /

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