7-11 August, 2006, San Diego, CA, USA. Visual Surveillance e.g. CCTV, is now an essential part of the urban infrastructure in modern cities. One of the primary aims in visual surveillance is to ensure a maximum visual coverage of an area with the least number of visual surveillance installations, which is a NP-Hard maximal coverage problem. The planning of visual surveillance is a highly sensitive and costly task that has traditionally been done with a gut-feel process of establishing sight lines in CAD software. This paper demonstrates the ArcView extension Isovist Analyst, which automatically identifies a minimal number of potential visual surveillance sites that ensure complete visual coverage of an area. The paper proposes a Stochastical Rank and Overlap Elimination (S-ROPE) method, which iteratively identifies the optimal visual surveillance sites. S-ROPE method is essentially based on a greedy search technique, which has been improved by a combination of selective sampling strategy and random initialisation
