Deformable template tracking in 1MS

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

Research output: Contribution to conferencePaperpeer-review

9 Scopus citations


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 nonrigid deformations. These deformations are mathematically modelled using 2D 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 [20], and show that the tracking precisions are similar but our method performs 100 times faster.

Original languageEnglish
StatePublished - 2014
Event25th British Machine Vision Conference, BMVC 2014 - Nottingham, United Kingdom
Duration: 1 Sep 20145 Sep 2014


Conference25th British Machine Vision Conference, BMVC 2014
Country/TerritoryUnited Kingdom


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