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7 July 1998 Multiresolution motion estimation and target detection
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Detecting and characterizing motion in a scene can play a critical role in target detection algorithms, since many targets can be camouflaged so completely that, if they are not moving, they are nearly undetectable. However, once they begin moving, they `popout' and are immediately detected. Estimating motion is also important in human vision modeling, because motion is generally detected with peripheral vision, which can cover the field of regard much more quickly than foveal vision. In this paper, we present two hierarchical multiresolution methods for computing the optical flow in a scene. We use statistical properties of the resulting flow fields to compute a motion feature vector, which we relate to the conspicuity of the moving target in a scene via a neural network.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert E. Karlsen, David J. Gorsich, and Grant R. Gerhart "Multiresolution motion estimation and target detection", Proc. SPIE 3375, Targets and Backgrounds: Characterization and Representation IV, (7 July 1998);

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