Jae-Deok Ha, Jinki Jung, Byungok Han, Kyusung Cho, H. Yang
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Mobile Augmented Reality using scalable recognition and tracking
In this paper, a new mobile Augmented Reality (AR) framework which is scalable to the number of objects being augmented is proposed. The scalability is achieved by a visual word recognition module on the remote server and a mobile phone which detects, tracks, and augments target objects with the received information from the server. The server and the mobile phone are connected through a conventional Wi-Fi. In the experiment, it takes 0.2 seconds for the cold start of an AR service initiation on a 10k object database, which is fairly acceptable in a real-world AR application.