The problem of camera placement has established an interesting challenge for the visual surveillance researchers. The broad target of the placement is to maximize the covered area with some sort of priority of the coverage. However, most of the current approaches perform the optimization task under the maximization condition. In contrast, those methods are neglecting the prioritization of the covered regions. The attempt here is to address the prioritization to support security monitoring. In this work, we present an underlying scheme to focus on the important zones within the area of interest. Thus, the monitored space is classified into multi-risk sub-zones. The product of the classification is known as Risk Map. According to the generated multi-level risk map, a greedy algorithm optimization is applied to locate the local maxima among the search domain. We believe that the risk mapping technique implemented in this work is capable of reflecting the variations in the monitoring requirements and offers expressive options to perform the camera placement to efficiently observe the area under investigation. © 2016 IEEE.