Automatic tracking of laparoscopic instruments by color coding
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real-Time Imaging - Special issue on multi-dimensional image processing
Keypoint Recognition Using Randomized Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Robotics Research
Articulated object tracking by rendering consistent appearance parts
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Segmentation and guidance of multiple rigid objects for intra-operative endoscopic vision
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Unified detection and tracking in retinal microsurgery
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
3D tracking of laparoscopic instruments using statistical and geometric modeling
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Region covariance: a fast descriptor for detection and classification
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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Tool tracking is an accepted capability for computer-aided surgical intervention which has numerous applications, both in robotic and manual minimally-invasive procedures. In this paper, we describe a tracking system which learns visual feature descriptors as class-specific landmarks on an articulated tool. The features are localized in 3D using stereo vision and are fused with the robot kinematics to track all of the joints of the dexterous manipulator. Experiments are performed using previously-collected porcine data from a surgical robot.