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M. Ayromlou, M. Zillich, W. Ponweiser, M. Vincze:
"Measuring Scene Complexity to Adapt Feature Selection of Model-based Object Tracking";
Talk: International Conference on Computer Vision Systems, Graz; 2003-04-01 - 2003-04-03; in: "Computer Vision Systems", (2003), ISBN: 3-540-00921-3; 448 - 459.

In vision-based robotic systems the robust tracking of scene
features is a key element of grasping, navigation and interpretation tasks.
The stability of feature initialisation and tracking is strongly influenced
by ambient conditions, like lighting and background, and their changes
over time. This work presents how robustness can be increased especially
in complex scenes by reacting to a measurement of the scene content. El-
ement candidates are proposed, to indicate the scene complexity remain-
ing after running a method. Local cue integration and global topological
constraints are applied to select the best feature set. Experiments show
in particular the success of the approach to disambiguate features in
complex scenes.

http://aleph.ub.tuwien.ac.at/F?base=tuw01&func=find-c&ccl_term=AC04404087