Robust Estimation of 3-D Camera Motion for . . .

We describe initial work on a system for augmenting video sequences with 3-D graphics or animations so that they appear to be present within the scene. Our aim is to do this in real-time for sequences captured by uncalibrated `live' cameras, such as a hand-held or wearable. These sequences typically contain jitter and can have narrow baselines between frames over extended time intervals. The paper focuses on obtaining accurate estimates of the 3-D motion and position of the camera for these types of sequences. We present a method based on sparse feature tracking and the recursive structure from motion algorithm developed by Azarbayejani and Pentland [1]. Our contribution is to report experiments which demonstrate that the approach performs well for sequences with jitter and narrow baselines and to discuss implementation issues relating to its use in a `live' real-time system