Abstract
Image sequence processing techniques are an essential tool for the experimental investigation of dynamical processes such as exchange, growth, and transport processes. These processes constitute much more complex motions than normally encountered in computer vision. In this paper, optical flow based motion analysis is extended into a generalized framework to estimate the motion field and the parameters of dynamic processes simultaneously. Examples from environmental physics and live sciences illustrate how this framework helps to tackles some key scientific questions that could not be solved without taking and analyzing image sequences. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Jähne, B. (2007). Complex motion in environmental physics and live sciences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3417 LNCS, pp. 91–103). Springer Verlag. https://doi.org/10.1007/978-3-540-69866-1_8
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