EKF monocular SLAM with relocalization for laparoscopic sequences
In recent years, research on visual SLAM has produced robust algorithms providing, in real time at 30 Hz, both the 3D model of the observed rigid scene and the 3D camera motion using as only input the gathered image sequence. These algorithms have been extensively validated in rigid human-made environments –indoor and outdoor– showing robust performance in dealing with clutter, occlusions or sudden motions. Medical endoscopic sequences naturally pose a monocular SLAM problem: an unknown camera motion in an unknown environment. The corresponding map would be useful in providing 3D information to assist surgeons, to support augmented reality insertions or to be exploited by medical robots. In this paper we propose the combination EKF Monocular SLAM + 1-Point RANSAC + Randomised List Relocalization to process laparoscopic sequences –abdominal cavity images–. The sequences are challenging due to: 1) cluttering produced by tools; 2) sudden motions of the camera; 3) laparoscope frequently goes in and out of abdominal cavity; 4) tissue deformation caused by respiration, heartbeats and/or surgical tools. Real medical image sequences provide experimental validation.
Oscar G. Grasa Javier Civera J. M. M. Montiel
Instituto de Investigaci(o)n e Ingenier(i)a de Arag(o)n,Universidad de Zaragoza,Spain
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
4816-4821
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）