Real-time scalable recognition and tracking based on the server-client model for mobile Augmented Reality
作者： Jaewon Ha , Kyusung Cho , Francisco A. Rojas , Hyun S. Yang
DOI: 10.1109/ISVRI.2011.5759649
关键词: Embedded system 、 Mobile computing 、 Mobile technology 、 Mobile device 、 Mobile search 、 Mobile telephony 、 Computer science 、 Augmented reality 、 Real-time computing 、 Mobile phone 、 Mobile database
摘要: Recent mobile device and vision technology advances have enabled Augmented Reality (AR) to be serviced in real-time using natural features. However, viewing augmented reality while moving about, the user is always encountering new diverse target objects different locations. Whether AR system scalable or not number of an important issue for future services. But this scalability has been far limited due small capacity internal storage memory devices. In paper, a framework proposed that achieves reality. The achieved by bag visual words based recognition module on server side with connected through conventional Wi-Fi. On client side, phone tracks augments features real-time. experiment, it takes 0.2 seconds cold start service initiated 10k object database accuracy 95%, which acceptable real-world application.
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