Optical EngineeringThree-dimensional attitude estimation and tracking with linear normalized optimal filtering
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We propose a 3-D target attitude estimation method based on linear optimal filtering and prediction algorithms. Through the use of correlation filters, the estimations of the 3-D attitude and scale of the target enable us to predict the temporal trajectory of the target and to perform a robust tracking. We propose a strategy to maintain a low number of correlations and thus to reduce the computational burden and the processing time. We demonstrate the efficiency of this approach in the case of optimal trade-off filters and sequences of noisy images.