Conference paper Open Access

VideoAnalysis4ALL: An On-line Tool for the Automatic Fragmentation and Concept-based Annotation, and the Interactive Exploration of Videos

Collyda, Chrysa; Apostolidis, Evlampios; Pournaras, Alexandros; Markatopoulou, Foteini; Mezaris, Vasileios; Patras, Ioannis


Citation Style Language JSON Export

{
  "DOI": "10.1145/3078971.3079015", 
  "author": [
    {
      "family": "Collyda, Chrysa"
    }, 
    {
      "family": "Apostolidis, Evlampios"
    }, 
    {
      "family": "Pournaras, Alexandros"
    }, 
    {
      "family": "Markatopoulou, Foteini"
    }, 
    {
      "family": "Mezaris, Vasileios"
    }, 
    {
      "family": "Patras, Ioannis"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2017, 
        6, 
        8
      ]
    ]
  }, 
  "abstract": "<p>This paper presents the VideoAnalysis4ALL tool that supports the automatic fragmentation and concept-based annotation of videos, and the exploration of the annotated video fragments through an interactive user interface. The developed web application decomposes the video into two different granularities, namely shots and scenes, and annotates each fragment by evaluating the existence of a number (several hundreds) of high-level visual concepts in the keyframes extracted from these fragments. Through the analysis the tool enables the identification and labeling of semantically coherent video fragments, while its user interfaces allow the discovery of these fragments with the help of human-interpretable concepts. The integrated state-of-the-art video analysis technologies perform very well and, by exploiting the processing capabilities of multi-thread / multi-core architectures, reduce the time required for analysis to approximately one third of the video\u2019s duration, thus making the analysis three times faster than real-time processing.</p>", 
  "title": "VideoAnalysis4ALL: An On-line Tool for the Automatic Fragmentation and Concept-based Annotation, and the Interactive Exploration of Videos", 
  "type": "paper-conference", 
  "id": "809700"
}
88
47
views
downloads
Views 88
Downloads 47
Data volume 471.4 MB
Unique views 85
Unique downloads 45

Share

Cite as