Automatic Viewpoint Switching for Multiview Surgical Videos Recording medical surgery operations is important for sharing the various operating techniques. In most operating rooms, fixed surgery cameras are already installed, but it is almost impossible to capture the surgical field because of occlusion by the surgeonxe2x80x99s head and body. In order to capture the surgical field in real surgery operations, we proposed the installation of multiple cameras in a surgical lighting system, so that at least one camera can capture the target surgical field even when the surgeonxe2x80x99s head and body occlude other cameras. In this paper, we present a method for automatic viewpoint selection from multiview surgical videos, so that the surgical field can always be recorded in the output video. We employ a method for learningbased object detection from videos for automatic evaluation of the surgical field area from multiple input videos. By selecting the viewpoint with the largest area of the surgical field, we can virtually reduce the area of the surgeonxe2x80x99s head and hands. In general, frequent camera switching degrades the video quality of view (QoV). Therefore, we apply the Dijkstra method widely used in the shortest path problem as a combinatorial optimization method for this problem. Our camera scheduling method is that the camera switching is not performed for a certain period of time, and the surgical field observed in the entire video is maximized.

optimizing MotionPlanning Problem Setup via Bounded Evaluation with Application to Following Surgical Trajectories A motionplanning problemxe2x80x99s setup can drastically affect the quality of solutions returned by the planner. In this work we consider optimizing these setups, with a focus on doing so in a computationallyefficient fashion. Our approach interleaves optimization with motion planning, which allows us to consider the actual motions required of the robot. Similar prior work has treated the planner as a black box: our key insight is that opening this box in a simpleyeteffective manner enables a more efficient approach, by allowing us to bound the work done by the planner to optimizerrelevant computations. Finally, we apply our approach to a surgicallyrelevant motionplanning task, where our experiments validate our approach by moreefficiently optimizing the fixed insertion pose of a surgical robot.