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Author
P. Mettes
J.C. van Gemert
S. Cappallo
T. Mensink
C.G.M. Snoek
Year
2015
Title
Bag-of-Fragments: Selecting and encoding video fragments for event detection and recounting
Event
2015 ACM International Conference on Multimedia Retrieval
Book/source title
ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China
Pages (from-to)
427-434
Publisher
New York, NY: Association for Computing Machinery
ISBN
9781450332743
Document type
Conference contribution
Faculty
Faculty of Science (FNWI)
Institute
Informatics Institute (IVI)
Abstract
The goal of this paper is event detection and recounting using a representation of concept detector scores. Different from existing work, which encodes videos by averaging concept scores over all frames, we propose to encode videos using fragments that are discriminatively learned per event. Our bag-of-fragments split a video into semantically coherent fragment proposals. From training video proposals we show how to select the most discriminative fragment for an event. An encoding of a video is in turn generated by matching and pooling these discriminative fragments to the fragment proposals of the video. The bag-of-fragments forms an effective encoding for event detection and is able to provide a precise temporally localized event recounting. Furthermore, we show how bag-of-fragments can be extended to deal with irrelevant concepts in the event recounting. Experiments on challenging web videos show that i) our modest number of fragment proposals give a high sub-event recall, ii) bag-of-fragments is complementary to global averaging and provides better event detection, iii) bag-of-fragments with concept filtering yields a desirable event recounting. We conclude that fragments matter for video event detection and recounting.
URL
go to publisher's site
Language
English
Permalink
http://hdl.handle.net/11245/1.478832

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