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Publication Detail
Robust real-time visual odometry for stereo endoscopy using dense quadrifocal tracking
  • Publication Type:
    Conference
  • Authors:
    Chang PL, Handa A, Davison AJ, Stoyanov D, Edwards PE
  • Publication date:
    01/01/2014
  • Pagination:
    11, 20
  • Published proceedings:
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Volume:
    8498 LNCS
  • ISBN-13:
    9783319075204
  • Status:
    Published
  • Print ISSN:
    0302-9743
Abstract
Visual tracking in endoscopic scenes is known to be a difficult task due to the lack of textures, tissue deformation and specular reflection. In this paper, we devise a real-time visual odometry framework to robustly track the 6-DoF stereo laparoscope pose using the quadrifocal relationship. The instant motion of a stereo camera creates four views which can be constrained by the quadrifocal geometry. Using the previous stereo pair as a reference frame, the current pair can be warped back by minimising a photometric error function with respect to a camera pose constrained by the quadrifocal geometry. Using a robust estimator can further remove the outliers caused by occlusion, deformation and specular highlights during the optimisation. Since the optimisation uses all pixel data in the images, it results in a very robust pose estimation even for a textureless scene. The quadrifocal geometry is initialised by using real-time stereo reconstruction algorithm which can be efficiently parallelised and run on the GPU together with the proposed tracking framework. Our system is evaluated using a ground truth synthetic sequence with a known model and we also demonstrate the accuracy and robustness of the approach using phantom and real examples of endoscopic augmented reality. © 2014 Springer International Publishing Switzerland.
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