Conference paper Open Access

Multimodal Video Annotation for Retrieval and Discovery of Newsworthy Video in a News Verication Scenario

Nixon, Lyndon; Apostolidis, Evlampios; Markatopoulou, Foteini; Patras, Ioannis; Mezaris, Vasileios


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>This paper describes the combination of advanced technologies for social-media-based story detection, story-based video retrieval and concept-based video (fragment) labeling under a novel approach for multimodal video annotation. This approach involves textual metadata, structural information and visual concepts - and a multimodal analytics dashboard that enables journalists to discover videos of news events, posted to social networks, in order to verify the details of the events shown. It outlines the characteristics of each individual method and describes how these techniques are blended to facilitate the content-based retrieval, discovery and summarization of (parts of) news videos. A set of case-driven experiments conducted with the help of journalists, indicate that the proposed multimodal video annotation mechanism - combined with a professional analytics dashboard which presents the collected and generated metadata about the news stories and their visual summaries - can support journalists in their content discovery and verication work.</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "MODUL Technology GmbH, Vienna, Austria", 
      "@type": "Person", 
      "name": "Nixon, Lyndon"
    }, 
    {
      "affiliation": "School of EECS, Queen Mary University of London, UK", 
      "@type": "Person", 
      "name": "Apostolidis, Evlampios"
    }, 
    {
      "affiliation": "Information Technologies Institute / Centre for Research & Technology Hellas,", 
      "@type": "Person", 
      "name": "Markatopoulou, Foteini"
    }, 
    {
      "affiliation": "School of EECS, Queen Mary University of London, UK", 
      "@type": "Person", 
      "name": "Patras, Ioannis"
    }, 
    {
      "affiliation": "Information Technologies Institute / Centre for Research & Technology Hellas,", 
      "@type": "Person", 
      "name": "Mezaris, Vasileios"
    }
  ], 
  "headline": "Multimodal Video Annotation for Retrieval and Discovery of Newsworthy Video in a News Verication Scenario", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2019-01-09", 
  "url": "https://zenodo.org/record/2539141", 
  "keywords": [
    "News video verication", 
    "Story detection", 
    "Video retrieval", 
    "Video fragmentation", 
    "Video annotation", 
    "Video summarization"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1007/978-3-030-05710-7_12", 
  "@id": "https://doi.org/10.1007/978-3-030-05710-7_12", 
  "@type": "ScholarlyArticle", 
  "name": "Multimodal Video Annotation for Retrieval and Discovery of Newsworthy Video in a News Verication Scenario"
}
18
15
views
downloads
Views 18
Downloads 15
Data volume 11.7 MB
Unique views 16
Unique downloads 11

Share

Cite as