Paper TRECVid Semantic Indexing of Video: A 6-Year Ret- rospective

Semantic indexing, or assigning semantic tags to video samples, is a key component for content-based access to video documents and collections. The Semantic Indexing task has been run at TRECVid from 2010 to 2015 with the support of NIST and the Quaero project. As with the previous High-Level Feature detection task which ran from 2002 to 2009, the semantic indexing task aims at evaluating methods and systems for detecting visual, auditory or multi-modal concepts in video shots. In addition to the main semantic indexing task, four secondary tasks were proposed namely the “localization” task, the “concept pair” task, the “no annotation” task, and the “progress” task. It attracted over 40 research teams during