Abstract
We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted information becomes enhanced by means of an unscented Kalman filtering process. It is a particular property of our algorithm to be able to deal with different kinds of visual descriptors by the very same mechanism. We show quantitative and qualitative results.
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Jessen, J.B., Pilz, F., Kraft, D., Pugeault, N., Krüger, N. (2011). Accumulation of Different Visual Feature Descriptors in a Coherent Framework. In: Heyden, A., Kahl, F. (eds) Image Analysis. SCIA 2011. Lecture Notes in Computer Science, vol 6688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21227-7_8
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DOI: https://doi.org/10.1007/978-3-642-21227-7_8
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