Abstract
In this paper we develop highly flexible Timoshenko beam model for tracking large deformations in noisy data. We demonstrate that by neglecting some physical properties of Timoshenko beam, classical energy beam can be derived. The comparison of these two models in terms of their robustness and precision against noisy data is given. We demonstrate that Timoshenko beam model is more robust and precise for tracking large deformations in the presence of clutter and partial occlusions. The experiments using both synthetic and real image data are performed. In synthetic images we fit both models to noisy data and use Monte Carlo simulation to analyze their performance. In real images we track deformations of the pole vault, the rat whiskers and the car antenna.
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Slobodan, I. (2007). Comparing Timoshenko Beam to Energy Beam for Fitting Noisy Data. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_6
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DOI: https://doi.org/10.1007/978-3-540-76386-4_6
Publisher Name: Springer, Berlin, Heidelberg
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