2011
DOI: 10.1117/12.898028
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Pose and class estimation of stationary ground vehicles using a scale augmented parameter set

Abstract: Automatic target recognition (ATR) has historically entailed the problems of detection, classification and tracking of ground or air targets from high resolution (imaging) sensor data as well as low resolution (radar) sensor data. A popular approach to solving the ATR problem is Bayesian inference, where detection (position and pose), classification and tracking are solved via a parameter estimation framework. The present paper offers a treatment of a subset of the aforementioned problem, which can be stated a… Show more

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