Paper Info
Title
Fast and Accurate Bronchoscope Tracking Using Image Registration and Motion Prediction
Abstract
This paper describes a method for faster and more accurate bronchoscope camera tracking by image registration and camera motion prediction using the Kalman filter. The position and orientation of the bronchoscope camera at a frame of a bronchoscopic video are predicted by the Kalman filter. Because the Kalman filter gives good prediction for image registration, estimation of the position and orientation of the bronchoscope tip converges fast and accurately. In spite of the usefulness of Kalman filters, there have been no reports on tracking bronchoscope camera motion using the Kalman filter. Experiments on eight pairs of real bronchoscopic video and chest CT images showed that the proposed method could track camera motion 2.5 times as fast as our previous method. Experimental results showed that the motion prediction increased the number of frames correctly and continuously tracked by about 4.5%, and the processing time was reduced by about 60% with the search space restriction also proposed in this paper.
Year
DOI
Venue
2004
10.1007/978-3-540-30136-3_68
Lecture Notes in Computer Science
Keywords
Field
DocType
image registration,kalman filter,search space
Computer vision,Pattern recognition,Computer science,Camera tracking,Kalman filter,Artificial intelligence,Motion prediction,Image registration
Conference
Volume
ISSN
Citations 
3217
0302-9743
14
PageRank 
References 
Authors
0.83
3
10
Name
Order
Citations
PageRank
Jiro Nagao1182.04
Kensaku Mori21125160.28
Tsutomu Enjouji3140.83
Daisuke Deguchi437762.03
Takayuki Kitasaka552067.91
Y Suenaga6737187.41
Jun-ichi Hasegawa722161.17
Jun-ichiro Toriwaki8578136.04
Hirotsugu Takabatake923529.60
Hiroshi Natori1022028.49