Share Email Print

Proceedings Paper

Keyframe selection for robust pose estimation in laparoscopic videos
Author(s): Udo von Öhsen; Jan Marek Marcinczak; Andres Felipe Mármol Vélez; Rolf-Rainer Grigat
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Motion estimation based on point correspondences in two views is a classic problem in computer vision. In the field of laparoscopic video sequences - even with state of the art algorithms - a stable motion estimation can not be guaranteed generally. Typically, a video from a laparoscopic surgery contains sequences where the surgeon barely moves the endoscope. Such restricted movement causes a small ratio between baseline and distance leading to unstable estimation results. Exploiting the fact that the entire sequence is known a priori, we propose an algorithm for keyframe selection in a sequence of images. The key idea can be expressed as follows: if all combination of frames in a sequence are scored, the optimal solution can be described as a weighted directed graph problem. We adapt the widely known Dijkstras Algorithm to find the best selection of frames.1 The framework for keyframe selection can be used universally to find the best combination of frames for any reliable scoring function. For instance, forward motion ensures the most accurate camera position estimation, whereas sideward motion is preferred in the sense of reconstruction. Based on the distribution and the disparity of point correspondences, we propose a scoring function which is capable of detecting poorly conditioned pairs of frames. We demonstrate the potential of the algorithm focusing on accurate camera positions. A robot system provides ground truth data. The environment in laparoscopic videos is reflected by an industrial endoscope and a phantom.

Paper Details

Date Published: 17 February 2012
PDF: 8 pages
Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83160Y (17 February 2012); doi: 10.1117/12.911381
Show Author Affiliations
Udo von Öhsen, Technische Univ. Hamburg-Harburg (Germany)
Jan Marek Marcinczak, Technische Univ. Hamburg-Harburg (Germany)
Andres Felipe Mármol Vélez, Technische Univ. Hamburg-Harburg (Germany)
Rolf-Rainer Grigat, Technische Univ. Hamburg-Harburg (Germany)

Published in SPIE Proceedings Vol. 8316:
Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes III; Kenneth H. Wong, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?