Product of tracking experts for visual tracking of surgical tools

Suren Kumar, Madusudanan Sathia Narayanan, Pankaj Singhal, Jason J. Corso, Venkat Krovi
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
more » ... robabilistic/non-probabilistic) from timevarying numbers of trackers. In the current implementation of PoTE, we use three tracking experts -point-feature-based, region-based and object detection-based. A novel point featurebased tracker is also proposed in the form of a voting based bounding box geometry estimation technique building upon point-feature correspondences. Our tracker is causal which makes it suitable for real-time applications. This framework has been tested on real surgical videos and is shown to significantly improve upon the baseline results.
doi:10.1109/coase.2013.6654037 dblp:conf/case/KumarNSCK13 fatcat:3co7edjkkvf57czaz6bmdha32e