Illumination Insensitive Template Matching with Hyperplanes

Data-driven object tracking is very important for many vision based applications, because it does not require any previous knowledge about the object to be tracked. In the literature, template matching techniques have successfully been used to solve this task. One promising descendant of these techniques is the hyperplane approach, which is both fast and robust. Unfortunately, like other template matching algorithms, it is inherently sensitive to illumination changes. In this paper, we describe three methods that considerably improve the illumination insensitivity of the hyperplane approach, while retaining the capability of real-time tracking. Experiments conducted on real image sequences prove the efficiency of our enhancements.