TY - GEN
T1 - Automatic viewpoint switching for multi-view surgical videos
AU - Shimizu, Tomohiro
AU - Oishi, Kei
AU - Saito, Hideo
AU - Kajita, Hiroki
AU - Takatsume, Yoshifumi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - 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 surgeon's 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 surgeon's head and body occlude other cameras. In this paper, we present a method for automatic viewpoint selection from multi-view surgical videos, so that the surgical field can always be recorded in the output video. We employ a method for learning-based 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 surgeon's 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.
AB - 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 surgeon's 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 surgeon's head and body occlude other cameras. In this paper, we present a method for automatic viewpoint selection from multi-view surgical videos, so that the surgical field can always be recorded in the output video. We employ a method for learning-based 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 surgeon's 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.
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U2 - 10.1109/ISMAR-Adjunct.2019.00037
DO - 10.1109/ISMAR-Adjunct.2019.00037
M3 - Conference contribution
AN - SCOPUS:85078775518
T3 - Adjunct Proceedings of the 2019 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019
SP - 89
EP - 90
BT - Adjunct Proceedings of the 2019 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019
Y2 - 14 October 2019 through 18 October 2019
ER -