Lim, JohnBarnes, Nicholas2015-12-10June 24-269781424422432http://hdl.handle.net/1885/49742We present a novel geometrical constraint on the egomotion of a single, moving camera. Using a camera with a large field-of-view (FOV), the optical flow measured at a single pair of antipodal points on the image sphere constrains the set of all possible camera motion directions to a subset region. By considering the flow at many such antipodal point pairs, it is shown that the intersection of all subset regions arising from each pair yields an estimate on the directions of motion. These antipodal point constraints rely on the geometrical properties of using a spherical representation of the image as well as the larger information content available from a large FOV. An algorithm using these constraints was implemented and tested on both simulated and real images. Results show comparable performance to the state of the art in the presence of noise and outliers whilst processing in constant time.Keywords: Artificial intelligence; Cameras; Computer vision; Feature extraction; Image processing; Optical flows; Pattern recognition; Antipodal points; Camera motions; Constant time; Ego-motion; Geometrical properties; Information contents; Large field-of-view; Mo200810.1109/CVPR.2008.45874972015-12-09