| Summary: | Thesis (M.Sc.)--Memorial University of Newfoundland, 2009. Computer Science Includes bibliographical references (leaves 77-81) Local visual homing is the process of determining the direction of movement required to return an agent to a goal location by comparing the current image with an image taken at the goal, known as the snapshot image. One way of accomplishing visual homing is by computing the correspondences between features and then analyzing the resulting flow field to determine the correct direction of motion. Typically, some strong assumptions need to be posited in order to compute the home direction from the flow field. For example, it is difficult to locally distinguish translation from rotation, so many authors assume rotation to be computable by other means (e.g. magnetic compass). We present a novel approach to visual homing using scale change information from the Scale Invariant Feature Transform (SIFT) which we use to compute landmark correspondences. The method we describe is able to determine the direction of the goal in the robot's frame of reference, irrespective of the relative 3D orientation with the goal.
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