We consider a bi-objective covering problem which is a close relative to the set covering problem. It is encountered in an application concerning cost-efficient camera surveillance of a bio-fuel depot. The two objectives are to simultaneously minimize the cost of the solution and to maximize its coverage, measured as the number of fulfilled covering constraints. These objectives are clearly in conflict, and for large scale instances it is very challenging and practically unfeasible to calculate the Pareto frontier. We propose a matheuristic approach to the problem. It aims at finding a near Pareto frontier in practically feasible computation times, and works by gradually constructing this frontier from zero coverage to full coverage. We apply the matheuristic to real-life instances and analyse its performance with respect to frontier quality metrics.