TY - GEN
T1 - Surgery recording without occlusions by multi-view surgical videos
AU - Shimizu, Tomohiro
AU - Oishi, Kei
AU - Hachiuma, Ryo
AU - Kajita, Hiroki
AU - Takatsume, Yoshihumi
AU - Saito, Hideo
N1 - Funding Information:
This research was funded by AMED research expenses (task number JP18he1902002h0001), JSTCREST (JPMJCR14E1, JPMJCR14E3), and Saitama Prefecture Leading-edge Industry Design Project.
Publisher Copyright:
Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Camera Scheduling
KW - Dijkstra’s Algorithm
KW - Multi-viewpoint Camera
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M3 - Conference contribution
AN - SCOPUS:85083503559
T3 - VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
SP - 837
EP - 844
BT - VISAPP
A2 - Farinella, Giovanni Maria
A2 - Radeva, Petia
A2 - Braz, Jose
PB - SciTePress
T2 - 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020
Y2 - 27 February 2020 through 29 February 2020
ER -