The advent of mobile phone with a multi-megapixel camera and autouploaders has democratised photography. Taking pictures and acquiring annotations is no longer an expensive task as it used to be. Yet performing these tasks in a systematically way is still very cumbersome for most users. In this paper, we outline two game mechanics that can be exploited for the purpose of large-scale image sensing and content annotation. Our first mechanic allows for better control over when, how and where people should acquire images. The problem with existent image providers is that their services usually do not cover the entire area of interest, are inaccurate or very expensive. Our second mechanism aims at making the annotation of crowd-sourcing images more engaging. It leverage on large end-user communities to annotate images while avoiding the pitfall of using annotations that are meaningful only to domain experts. Annotations that are not relevant to users’ interests cannot be directly leveraged to enable search and discovery. A drawback of using crowdsourced annotations is that they have low agreement rates. Our approach aims at a finding a balanced agreement rate between pre-established annotations and those defined by users.
Djaouti, D., Alvarez, J., Jessel, J.-P., Rampnoux, O.: Origins of serious games. In: Serious Games and Edutainment Applications, pp. 25–43. Springer (2011)