In this paper we present a system for content-based video recommendation that exploits visual saliency to better represent video features and content. Visual saliency is used to select relevant frames to be presented in a web-based interface to tag and annotate video frames in a social network; it is also employed to summarize video content to create a more effective video representation used in the recommender system. The system exploits automatic annotations from CNN-based classifiers on salient frames and user generated annotations. We evaluate several baseline approaches and show how the proposed method improves over them.

A System for Video Recommendation Using Visual Saliency, Crowdsourced and Automatic Annotations / Ferracani, Andrea; Pezzatini, Daniele; Bertini, Marco; Meucci, Saverio; Del Bimbo, Alberto. - STAMPA. - (2015), pp. 757-758. (Intervento presentato al convegno ACM Multimedia International Conference) [10.1145/2733373.2807982].

A System for Video Recommendation Using Visual Saliency, Crowdsourced and Automatic Annotations

FERRACANI, ANDREA;PEZZATINI, DANIELE;BERTINI, MARCO;DEL BIMBO, ALBERTO
2015

Abstract

In this paper we present a system for content-based video recommendation that exploits visual saliency to better represent video features and content. Visual saliency is used to select relevant frames to be presented in a web-based interface to tag and annotate video frames in a social network; it is also employed to summarize video content to create a more effective video representation used in the recommender system. The system exploits automatic annotations from CNN-based classifiers on salient frames and user generated annotations. We evaluate several baseline approaches and show how the proposed method improves over them.
2015
Proceedings of the 23rd ACM International Conference on Multimedia
ACM Multimedia International Conference
Ferracani, Andrea; Pezzatini, Daniele; Bertini, Marco; Meucci, Saverio; Del Bimbo, Alberto
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1036437
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