Large scale video surveillance systems are becoming more and more ubiquitous. Studies have suggested, however, that camera placement can be inadequate, and that this can significantly afflict system effectiveness. This paper proposes an optimizing framework for the automatic placement of a variable number of cameras in arbitrary complex environments. This framework uses a multi-objective evolutionary algorithm to produce a pareto-optimal set of solutions expressing different cost/performance compromises. Results are presented for different camera placement problems.