Abstract
The access to large-scale imagery datasets has been a significant obstacle to the success of many applications in application domains that range from 3D modelling to augmented reality, and from infrastructure inspection to urban planning. Although large collections of images already exist, from sources such as Bing Maps, Google Street View, and many photo-sharing sites, they are incomplete, inaccurate and expensive. A solution to this problem could be to leverage on large end-user communities to collaboratively acquire and share information about their surroundings. In this paper, we outline some basic mechanics in serious games that can be explored for the purpose of data collection. Additionally, we describe new ways of guiding players’ actions towards the purpose of our game – image and video crowdsourcing.
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Acknowledgements
This research has been supported by the European Commission (EC) under the project c-Space (Grant Agreement N. 611040). The authors are solely responsible for the content of the paper. It does not represent the opinion of the European Community. The European Community is not responsible for any use that might be made of information contained herein. Special thanks should also be given to Matteo Eccher (Graphitech), Luca Baldesi (University of Trento), and Laura Cattoni (MUSE) for their contribution to the gameplay mentioned in this paper.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Simões, B., Bianchi, M., Debiasi, A., De Amicis, R. (2016). Serious Games for Large-Scale Image Sensing. In: Vaz de Carvalho, C., Escudeiro, P., Coelho, A. (eds) Serious Games, Interaction, and Simulation. 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 161. Springer, Cham. https://doi.org/10.1007/978-3-319-29060-7_17
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DOI: https://doi.org/10.1007/978-3-319-29060-7_17
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