Abstract
A new robust matching algorithm for motion detection and computation of precise estimates of motion vectors of moving objects in a sequence of images is presented. Common matching algorithms of dynamic image analysis usually utilize local smoothness constraints. The proposed method exploits global motion smoothness. The suggested matching algorithm is robust to motion discontinuity as well as to noise degradation of a signal. Computer simulation and experimental results demonstrate an excellent performance of the method in terms of dynamic motion analysis.
Keywords
- Optical Flow
- Motion Vector
- Smoothness Constraint
- Dissimilarity Function
- Motion Vector Field
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Mozerov, M., Kober, V. (2005). A Robust Matching Algorithm Based on Global Motion Smoothness Criterion. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_31
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DOI: https://doi.org/10.1007/11578079_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)
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