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Product of tracking experts for visual tracking of surgical tools
2013
2013 IEEE International Conference on Automation Science and Engineering (CASE)
This paper proposes a novel tool detection and tracking approach using uncalibrated monocular surgical videos for computer-aided surgical interventions. We hypothesize surgical tool end-effector to be the most distinguishable part of a tool and employ state-of-the-art object detection methods to learn the shape and localize the tool in images. For tracking, we propose a Product of Tracking Experts (PoTE) based generalized object tracking framework by probabilistically-merging tracking outputs
doi:10.1109/coase.2013.6654037
dblp:conf/case/KumarNSCK13
fatcat:3co7edjkkvf57czaz6bmdha32e