Coverage is an important metric for evaluating the sensing quality of visual sensor networks (VSNs). Unlike traditional coverage issues

full-view coverage requires to capture target’s effective face from any direction

and its coverage estimation issue is more complicated. At present

most of literatures assume that a great number of homogeneous visual sensors are randomly scattered in the monitoring area to achieve full-view. This paper studies the full-view estimation problem in heterogeneous VSNs. In order to eliminate the boundary effect

the concepts of extended monitoring area and maximum detection area are introduced. To evaluate the performance of the proposed full-view estimation expression

several simulation experiments are conducted to validate the theoretical results. The results show that the mean absolute coverage error between the theoretical values and the experimental values is controlled less than 6.5%.