Abstract
This paper deals with the problem of locating a rigid object and estimating its motion in three dimensions. This involves determining the position and orientation of the object at each instant when an image is captured by a camera, and recovering the motion of the object between consecutive frames.
In the implementation scheme used here, a sequence of camera images, digitized at the sample instants, is used as the initial input data. Measurements are made of the locations of certain features (e.g., maximum curvature points of an image contour, corners, edges, etc.) on the 2-D images. To measure the feature locations a matching algorithm is used, which produces correspondences between the features in the image and the object.
Using the measured feature locations on the image, an algorithm is developed to solve the location and motion problem. The algorithm is an extended Kalman filter modeled for this application.
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Department of Electrical Engineering and Alberta Center for Machine Intelligence and Robotics, University of Alberta
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Wu, J.J., Rink, R.E., Caelli, T.M. et al. Recovery of the 3-D location and motion of a rigid object through camera image (An Extended Kalman Filter Approach). Int J Comput Vision 2, 373–394 (1989). https://doi.org/10.1007/BF00133556
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DOI: https://doi.org/10.1007/BF00133556