TY - CHAP U1 - Konferenzveröffentlichung A1 - Scheytt, Josia A1 - Wiemuth, Markus A1 - Burgert, Oliver ED - Burgner-Kahrs, Jessica T1 - Binary endoscope localization from laparoscopic video as virtual sensor for automatic workflow detection T2 - CURAC 2017 - Tagungsband : 16. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) : 5.-7. Oktober 2017, Hannover N2 - This paper contributes to the automatic detection of perioperative workflow by developing a binary endoscope localization. Automated situation recognition in the context of an intelligent operating room requires the automatic conversion of low level cues into more abstract high level information. Imagery from a laparoscope delivers rich content that is easy to obtain but hard to process. We introduce a system which detects if the endoscope's distal tip is inside or outsiede the patient based on the endoscope video. This information can be used as one parameter in a situation recognition pipeline. Our localization performs in real-time at a video resolution of 1280x720 and 5-fold cross validation yields mean F1-scores of up to 0,94 on videos of 7 laparoscopies. KW - endoscope localization KW - situation recognition KW - laparoscopic surgery Y1 - 2017 UR - https://www.curac.org/images/advportfoliopro/images/CURAC2017/2017_CURAC_Tagungsband_Compiled_V1.7_final.pdf SN - 978-3-95900-158-8 SB - 978-3-95900-158-8 SP - 191 EP - 196 S1 - 6 PB - Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e. V. CY - Stuttgart ER -