@inproceedings {PN6509,
	title = {Demand-Driven Visual Information Acquisition},
	author = {Sven Rebhan AND Andreas Richter AND Julian Eggert},
	year = {2009},
	abstract = {Fast, reliable and demand-driven acquisition of visual information is the key to represent visual scenes efficiently. To achieve this efficiency, a cognitive vision system must plan the utilization of its processing resources to acquire only information relevant for the task. Here, the incorporation of long-term knowledge plays a major role on deciding which information to gather. In this paper, we present a first approach to make use of the knowledge about the world and its structure to plan visual actions. We propose a method to schedule those visual actions to allow for a fast discrimination between objects that are relevant or irrelevant for the task. By doing so, we are able to reduce the system{\textquoteright}s computational demand. A first evaluation of our ideas is given using a proof-of-concept implementation.},
	publisher = {Springer},
	booktitle = {Proceedings of the 7th International Conference on Computer Vision Systems (ICVS)},
	editor = {Mario Fritz and Bernt Schiele and Justus H. Piater},
	pages = {124{\textendash}133},
	series = {Lecture Notes in Computer Science}
}