Event retrieval in large video collections with circulant temporal encoding - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

Event retrieval in large video collections with circulant temporal encoding

Résumé

This paper presents an approach for large-scale event retrieval. Given a video clip of a specific event, e.g., the wedding of Prince William and Kate Middleton, the goal is to retrieve other videos representing the same event from a dataset of over 100k videos. Our approach encodes the frame descriptors of a video to jointly represent their appearance and temporal order. It exploits the properties of circulant matrices to compare the videos in the frequency domain. This offers a significant gain in complexity and accurately localizes the matching parts of videos. Furthermore, we extend product quantization to complex vectors in order to compress our descriptors, and to compare them in the compressed domain. Our method outperforms the state of the art both in search quality and query time on two large-scale video benchmarks for copy detection, Trecvid and CCweb. Finally, we introduce a challenging dataset for event retrieval, EVVE, and report the performance on this dataset.
Fichier principal
Vignette du fichier
revaud_event.pdf (1.56 Mo) Télécharger le fichier
Vignette du fichier
eventretrieval.png (16.43 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Loading...

Dates et versions

hal-00801714 , version 1 (18-03-2013)

Identifiants

Citer

Jérôme Revaud, Matthijs Douze, Cordelia Schmid, Hervé Jégou. Event retrieval in large video collections with circulant temporal encoding. CVPR 2013 - International Conference on Computer Vision and Pattern Recognition, Jun 2013, Portland, United States. pp.2459-2466, ⟨10.1109/CVPR.2013.318⟩. ⟨hal-00801714⟩
3546 Consultations
2933 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More