Deformable Template Tracking in 1ms

David Joseph Tan, Stefan Holzer, Nassir Navab and Slobodan Ilic

In Proceedings British Machine Vision Conference 2014


We address the problem of real-time deformable template tracking. Our approach relies on linear predictors which establish a linear relation between the image intensity differences of a template and the corresponding template transformation parameters. Up to this work, linear predictors have only been used to handle linear transformations such as homographies to track planar surfaces. In this paper, we introduce a method to learn non-linear template transformations that allows us to track surfaces that undergo non-rigid deformations. These deformations are mathematically modelled using $2$D Free Form Deformations. Moreover, the simplicity of our approach allows us to track deformable surfaces at extremely high speed of approximately $1$~ms per frame that has never been shown before. To evaluate our algorithm, we perform an extensive analysis of our method's performance on synthetic and real sequences with different types of surface deformations. In addition, we compare our results from the real sequences to the feature-based tracking-by-detection method \cite{pilet2008fast}, and show that the tracking precisions are similar but our method performs 100 times faster.




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Bibtex File



David Joseph Tan, Stefan Holzer, Nassir Navab, and Slobodan Ilic. Deformable Template Tracking in 1ms. Proceedings of the British Machine Vision Conference. BMVA Press, September 2014.


	title = {Deformable Template Tracking in 1ms},
	author = {Joseph Tan, David and Holzer, Stefan and Navab, Nassir and Ilic, Slobodan},
	year = {2014},
	booktitle = {Proceedings of the British Machine Vision Conference},
	publisher = {BMVA Press},
	editors = {Valstar, Michel and French, Andrew and Pridmore, Tony}
	doi = { }