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research-article

Event-based media processing and analysis

Authors:

Christos Tzelepis,

Vasileios Mezaris,

Bogdan Ionescu,

Ioannis Kompatsiaris,

Shuicheng YanAuthors Info & Claims

Image and Vision Computing, Volume 53, Issue C

Pages 3 - 19

https://doi.org/10.1016/j.imavis.2016.05.005

Published: 01 September 2016 Publication History

Abstract

Research on event-based processing and analysis of media is receiving an increasing attention from the scientific community due to its relevance for an abundance of applications, from consumer video management and video surveillance to lifelogging and social media. Events have the ability to semantically encode relationships of different informational modalities, such as visual-audio-text, time, involved agents and objects, with the spatio-temporal component of events being a key feature for contextual analysis. This unveils an enormous potential for exploiting new information sources and opening new research directions. In this paper, we survey the existing literature in this field. We extensively review the employed conceptualization of the notion of event in multimedia, the techniques for event representation and modeling, the feature representation and event inference approaches for the problems of event detection in audio, visual, and textual content. Furthermore, we review some key event-based multimedia applications, and various benchmarking activities that provide solid frameworks for measuring the performance of different event processing and analysis systems. We provide an in-depth discussion of the insights obtained from reviewing the literature and identify future directions and challenges. We survey the literature in event-based media processing and analysis.We examine the different definitions of events.We study various techniques for event representation and modeling.We survey feature representation, event inference approaches in multimedia content.We review event-based multimedia applications and various benchmarking activities.

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cover image Image and Vision Computing

Image and Vision Computing Volume 53, Issue C

September 2016

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Ahmad KPogorelov KRiegler MConci NHalvorsen P(2019)Social media and satellitesMultimedia Tools and Applications10.1007/s11042-018-5982-978:3(2837-2875)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11042-018-5982-9
Saeed ZAbbasi RMaqbool OSadaf ARazzak IDaud AAljohani NXu G(2019)What's Happening Around the World? A Survey and Framework on Event Detection Techniques on TwitterJournal of Grid Computing10.1007/s10723-019-09482-217:2(279-312)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10723-019-09482-2
Dao MQuang Nhat Minh PKasem AHaja Nazmudeen MAizawa KLew MSatoh S(2018)A Context-Aware Late-Fusion Approach for Disaster Image Retrieval from Social MediaProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206047(266-273)Online publication date: 5-Jun-2018
https://dl.acm.org/doi/10.1145/3206025.3206047
Ahmad KMekhalfi MConci NMelgani FNatale F(2018)Ensemble of Deep Models for Event RecognitionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/319966814:2(1-20)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1145/3199668
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