Recording surgery is important for sharing various operating techniques. In most surgical rooms, fixed surgical cameras are already installed, but it is almost impossible to capture the surgical field because of occlusion by the surgeon’s head and body. In order to capture the surgical field, we propose the installation of multiple cameras in a surgical lamp system, so that at least one camera can capture the surgical field even when the surgeon’s head and body occlude other cameras. In this paper, we present a method for automatic viewpoint switching from multi-view surgical videos, so that the surgical field can always be recorded. We employ a method for learning-based object detection from videos for automatic evaluation of the surgical field from multi-view surgical videos. In general, frequent camera switching degrades the video quality of view (QoV). Therefore, we apply Dijkstra’s algorithm, widely used in the shortest path problem, as an optimization method for this problem. Our camera scheduling method works so that camera switching is not performed for the minimum frame we specified, and therefore the surgical field observed in the entire video is maximized.