Topics in matrix analysis
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerische Isotropieoptimierung von FIR-Filtern mittels Querglättung
Mustererkennung 1997, 19. DAGM-Symposium
A System-Theoretical View on Local Motion Estimation
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
Errors-in-variables modeling in optical flow estimation
IEEE Transactions on Image Processing
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Filtering a signal with a finite impulse response (FIR) filter introduces dependencies between the errors in the filtered image due to overlapping filter masks. If the filtering only serves as a first step in a more complex estimation problem (e.g. orientation estimation), then these correlations can turn out to impair estimation quality. The aim of this paper is twofold. First, we show that orientation estimation (with estimation of optical flow being an important special case for space-time volumes) is a Total Least Squares (TLS) problem: Tp$\thickapprox$0 with sought parameter vector p and given TLS data matrix T whose statistical properties can be described with a covariance tensor. In the second part, we will show how to improve TLS estimates given this statistical information.