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[SFC15] Fast action localization in large scale video archives
Revue Internationale avec comité de lecture : Journal IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), vol. 26(10), pp. 1917-1930, 2015, (doi:10.1109/TCSVT.2015.2475835)Mots clés: action localization, detector cascade, global alignment, scalability, feature selection
Résumé:
Finding content in large video archives has so far
required textual annotation to enable search by keywords. Our
aim is to support retrieval from such archives using queries
based on example video clips which contain meaningful human
actions.We propose a solution for the scalable search of actions in
large-scale archives by leveraging the complementarity between
the description at the frame level and the aggregation in time
of descriptors. To permit fast search we introduce a two-level
cascade. The inexpensive first level employs aggregation to filter
out a large part of the video. At the second level, aided by feature
selection, a more discriminative comparison by frame alignment
ranks the remaining video sequences. We improve upon the state
of the art on popular data sets and we introduce and show results
on a novel video archive data set that is significantly larger than
previous ones.
Equipe:
vertigo
Collaboration:
LaBRI
BibTeX
| @article { | |||
| SFC15, | |||
| title | = | "{Fast action localization in large scale video archives}", | |
| author | = | "A. Stoian and M. Ferecatu and M. Crucianu and J. Benois-Pineau", | |
| journal | = | "IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT)", | |
| year | = | 2015, | |
| volume | = | 26, | |
| number | = | 10, | |
| pages | = | "1917-1930", | |
| doi | = | "10.1109/TCSVT.2015.2475835", | |
| } | |||
