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17 August 2000 Geometric parameter estimation with a multiscale template library
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A common image processing problem is determining the location of an object using a template when the size and rotation of the object are unknown. In the case of known geometric parameters, it is possible to use an impulse reconstruction technique to determine object location. In the case of unknown parameters, we show that localization is possible by computing a likelihood surface for a dense sampling of the size and rotation space. However, the surface produced is not amenable to conventional minimization methods due to local minima and regions of small or zero gradient. Using a smooth approximate template, we can overcome these difficulties at the expense of estimation accuracy. We therefore demonstrate a technique which employs a library of templates starting from the smooth approximation and adding detail until the exact template is reached. Successively estimating the geometric parameters using these templates achieves the accuracy of the exact template while remaining within a well-behaved 'bowl' in the search space which allows standard minimization techniques to be used.
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Roger M. Dufour, Eric L. Miller, and Nikolas P. Galatsanos "Geometric parameter estimation with a multiscale template library", Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000);

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