Rapid selection of reliable templates for visual tracking

We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such as SLAM, where it is essential to track a low number of preferably reliable templates. Our approach is based on simple i...

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Bibliographic Details
Published in2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition pp. 1355 - 1362
Main Authors Alt, Nicolas, Hinterstoisser, Stefan, Navab, Nassir
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2010
Subjects
Algorithm design and analysis
Application software
Biomedical imaging
Convergence
Feature extraction
Image motion analysis
Linear approximation
Robustness
Runtime
Target tracking
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Summary:We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such as SLAM, where it is essential to track a low number of preferably reliable templates. Our approach is based on simple image features specifically designed to identify texture properties which are problematic for tracking. During a training step, a support vector régresser is learned. It uses a tracking quality measure which considers both convergence rate and speed obtained by simulation of many tracking attempts. Finally, a minimum set of image features is identified to speedup the online selection process. In experiments on real-world video sequences our method improved the detection rate of an existing tracking-by-detection system by 8% on average.
ISBN:1424469848
9781424469840
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2010.5539812