Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Outdoors augmented reality on mobile phone using loxel-based visual feature organization
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Going out: robust model-based tracking for outdoor augmented reality
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
An Augmented Reality museum guide
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
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Typical photo-based augmented reality applications match photos against contents in a database of images, using image retrieval algorithms. Further, in such augmented reality applications, content authoring is a tedious and expensive task that requires specialized skills. Consequently, scaling database contents is hard, which results in lack of data sets to be recognized and even reduces accuracy in recognizing objects. We propose a mobile augmented reality software framework that enhances scalability of contents by using human computation resources. We utilize social network services as resources for our system, which collect image content generated by active users in social network services such as Twitter. As a result, we provide very large and scalable database of contents. We demonstrate that our new system is not only feasible but a practical solution.