Title: Automated Placement of Cameras in a Floorplan to Satisfy Task-Specific
Constraints
Authors: Ugur Murat Erdem and Stan Sclaroff
Abstract:
In many multi-camera vision systems the effect of camera locations on the
task-specific quality of service is ignored. Researchers in Computational
Geometry have proposed elegant solutions for some sensor location problem
classes. Unfortunately, these solutions utilize unrealistic assumptions
about the cameras' capabilities that make these algorithms unsuitable for
many real-world computer vision applications: unlimited field of view,
infinite depth of field, and/or infinite servo precision and speed. In
this paper, the general camera placement problem is first defined with
assumptions that are more consistent with the capabilities of real-world
cameras. The region to be observed by cameras may be volumetric, static or
dynamic, and may include holes that are caused, for instance, by columns or
furniture in a room that can occlude potential camera views. A subclass of
this general problem can be formulated in terms of planar regions that are
typical of building floorplans. Given a floorplan to be observed, the
problem is then to efficiently compute a camera layout such that certain
task-specific constraints are met. A solution to this problem is obtained
via binary optimization over a discrete problem space. In preliminary
experiments the performance of the resulting system is demonstrated with
different real floorplans.