Abstract.
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 pro jected from planar 3D patches (pla- nar features), by enforcing a conservative threshold on the residual of the difference between the warped current feature and the reference. How- ever, 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 fea- tures containing occluding boundaries then becomes an interesting goal, for which we propose a multi-scale monitoring solution striving to maxi- mize the lifetime of the feature, while also detecting the tracking failures. The devised technique infers the parts of the reference which are not pro- jected 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 tech- nique is effective in increasing the average feature lifetimes, especially in sequences with occlusions and large photometric variations.