A collaborative approach for semantic time-based video annotation using gamification

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ID: 94593
2017
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Abstract
Abstract Efficient access to large scale video assets, may it be our life memories in our hard drive or a broadcaster archive which the company is eager to sell, requires content to be conveniently annotated. Manually annotating video content is, however, an intellectually expensive and time-consuming process. In this paper we argue that crowdsourcing, an approach that relies on a remote task force to perform activities that are costly or time-consuming using traditional methods, is a suitable alternative and we describe a solution based on gamification mechanisms for collaboratively collecting timed metadata. Tags introduced by registered players are validated based on a collaborative scoring mechanism that excludes erratic annotations. Voting mechanisms, enabling users to approve or refuse existing tags, provide an extra guarantee on the quality of the annotations. The sense of community is also created as users may watch the crowd’s favourite moments of the video provided by a summarization functionality. The system was tested with a pool of volunteers in order to evaluate the quality of the contributions. The results suggest that crowdsourced annotation can describe objects, persons, places, etc. correctly, as well as be very accurate in time.
Reference Key
viana2017ahumancentric Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Viana, Paula;Pinto, José Pedro;
Journal human-centric computing and information sciences
Year 2017
DOI
DOI not found
URL
http://link.springer.com/article/10.1186/s13673-017-0094-5
Keywords
chemistry Medicine (General) Chemical technology Technology environmental effects of industries and plants renewable energy sources environmental sciences business education (general) social sciences history (general) and history of europe electronic computers. computer science political science (general) theory and practice of education information theory

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