Enhancing the Point Feature Tracker by Adaptive Modelling of the Feature Support

  • Siniša Šegvić
  • Anthony Remazeilles
  • François Chaumette
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3952)


We consider the problem of tracking a given set of point features over large sequences of image frames. A classic procedure for monitoring the tracking quality consists in requiring that the current features nicely warp towards their reference appearances. The procedure recommends focusing on features projected from planar 3D patches (planar features), by enforcing a conservative threshold on the residual of the difference between the warped current feature and the reference. However, in some important contexts, there are many features for which the planarity assumption is only partially satisfied, while the true planar features are not so abundant. This is especially true when the motion of the camera is mainly translational and parallel to the optical axis (such as when driving a car along straight sections of the road), which induces a permanent increase of the apparent feature size. Tracking features containing occluding boundaries then becomes an interesting goal, for which we propose a multi-scale monitoring solution striving to maximize the lifetime of the feature, while also detecting the tracking failures. The devised technique infers the parts of the reference which are not projected from the same 3D surface as the patch which has been consistently tracked until the present moment. The experiments on real sequences taken from cars driving through urban environments show that the technique is effective in increasing the average feature lifetimes, especially in sequences with occlusions and large photometric variations.


Median Absolute Deviation Adaptive Modelling Visual Servoing Error Image Feature Support 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Siniša Šegvić
    • 1
  • Anthony Remazeilles
    • 2
  • François Chaumette
    • 1
  1. 1.IRISA/INRIA Rennes, Campus de BeaulieuRennesFrance
  2. 2.IRISA/INSA Rennes, Campus de BeaulieuRennesFrance

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