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. © 2011 Springer-Verlag.
CITATION STYLE
Jessen, J. B., Pilz, F., Kraft, D., Pugeault, N., & Krüger, N. (2011). Accumulation of different visual feature descriptors in a coherent framework. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6688 LNCS, pp. 79–90). https://doi.org/10.1007/978-3-642-21227-7_8
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