On the use of semantic technologies for video analysis

Tracking #: 1789-3002

This paper is currently under review
Pierluigi Ritrovato
Luca Greco
Mario Vento

Responsible editor: 
Guilin Qi

Submission type: 
Survey Article
The rapid proliferation of video recording devices has led to a huge explosion of contents, determining an ever increasing interest towards the development of methods and tools for automatic video analysis and interpretation. Through the years, the availability of contextual knowledge has proven to improve video analysis algorithms' performances in several ways, although the formal representation of semantic content in a shareable and fusion oriented manner is still an open problem. In this context, an interesting answer has come from Semantic technologies, that opened a new interesting perspective for the so called Knowledge Based Computer Vision (KBCV), adding new functionality, improving accuracy, and facilitating data exchange between video analysis systems in an open extensible manner. In this work, we propose a survey of the papers from the last fifteen years, back when first applications of semantic technologies to video analysis have appeared. The papers have been analyzed under different perspectives leading to the definition of a taxonomy of the different approaches and the semantic web technology stack adoption. As a result, some insights about current trends and future challenges are provided too.
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