Abstract. In this paper, we propose intuitive motion-based interfaces for map navigation on mobile devices with built-in cameras. The interfaces are based on the visual detection of the devices self-motion. This gives people the experience of navigating maps with a virtual looking glass. We conducted a user study to evaluate the accuracy, sensitivity and responsiveness of our proposed system. Results show that users appreciate our motion-based user interface and find it more intuitive than traditional key-based controls, even though there is a learning curve. Key words: Virtual map navigation, user interface, motion detection, pose estimation. 1

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping. 1.