In 2009, Klein proposed a keyframe-based simultaneous localization and mapping (SLAM)
system on a camera phone [7]. Figure 5 displays the sample results. Nevertheless, this system still suffers from the issues of speed and frame-rate. This means that the computational time for the algorithm is high. By applying PTAM, an egomotion estimation algorithm for an Android Smartphone was recently proposed by Porzi [9] in September 2012. This research used an Extended Kalman Filter for improving localization accuracy integrating the information from inertial sensors for supporting his augmented reality applications. Similar research for data association and finding camera trajectory using SLAM for outdoor augmented reality can be also found in [10] by Erkan et al.