Add to ORKGInternational audienceIn this paper, we compare active learning strategies for indexing concepts in video shots. Active learning is simulated using subsets of a fully annotated dataset instead of actually calling for user intervention. Training is done using the collaborative annotation of 39 concepts of the TRECVID 2005 campaign. Performance is measured on the 20 concepts selected for the TRECVID 2006 concept detection task. The simulation allows exploring the effect of several parameters: the strategy, the annotated fraction of the dataset, the number of iterations and the relative difficulty of concepts
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The authors developed an extensible system for video exploitation that puts the user in control to b...
International audienceIn this paper, we compare active learning strategies for indexing concepts in ...
Published online in September 2010: http://link.springer.com/content/pdf/10.1007%2Fs11042-010-0599-7...
Regular Papers: Multimedia Indexing and MiningInternational audienceActive learning with multiple cl...
The general framework of this thesis is semantic indexing and information retrieval, applied to mult...
Le cadre général de cette thèse est l'indexation sémantique et la recherche d'informations, appliqué...
Video indexing, also called video concept detection, has attracted increasing attentions from both a...
Session MultimédiaNational audienceVideo retrieval can be done by ranking the samples according to t...
International audienceConcept indexing in multimedia libraries is very useful for users searching an...
Poster PapersNational audienceIn this paper, we have described the Active Cleaning approach that was...
International audienceIn this paper, we evaluated and compared multi-learner approaches for concept ...
Conventional multimedia annotation/retrieval systems such as Normalized Continuous Relevance Model (...
Existing video search engines have not taken the advantages of video content analysis and semantic u...
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The authors developed an extensible system for video exploitation that puts the user in control to b...
International audienceIn this paper, we compare active learning strategies for indexing concepts in ...
Published online in September 2010: http://link.springer.com/content/pdf/10.1007%2Fs11042-010-0599-7...
Regular Papers: Multimedia Indexing and MiningInternational audienceActive learning with multiple cl...
The general framework of this thesis is semantic indexing and information retrieval, applied to mult...
Le cadre général de cette thèse est l'indexation sémantique et la recherche d'informations, appliqué...
Video indexing, also called video concept detection, has attracted increasing attentions from both a...
Session MultimédiaNational audienceVideo retrieval can be done by ranking the samples according to t...
International audienceConcept indexing in multimedia libraries is very useful for users searching an...
Poster PapersNational audienceIn this paper, we have described the Active Cleaning approach that was...
International audienceIn this paper, we evaluated and compared multi-learner approaches for concept ...
Conventional multimedia annotation/retrieval systems such as Normalized Continuous Relevance Model (...
Existing video search engines have not taken the advantages of video content analysis and semantic u...
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The usual techniques of video indexing generally go through a learning phase that requires the prior...
The authors developed an extensible system for video exploitation that puts the user in control to b...