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PCA-based 3D Pose Modeling for Beating Heart Tracking

Bo Yang 1 Chao Liu 2 Wenfeng Zheng 1
2 DEXTER - Conception et commande de robots pour la manipulation
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : A statistical pose model is developed for efficient 3D visual tracking of beating heart. The Region of Interest (ROI) on heart surfaces is first pre-tracked with a conventional high-order thin plate spline model. The 3D pose data of the ROI extracted from the pre-tracked results are then used to train a low-order 3D pose model based on the principal component of these pose data. The low-order model is accurate, robust, and efficient for tracking subsequent heart motion as heart beats are quasi-periodic with stable statistics and the redundant degree of freedom for fitting the poses of heart surface is significantly decreased by the principalcomponent-based dimensionality reduction. The proposed 3D pose modeling is validated on the stereo-endoscopic videos recorded by the da Vinci® surgical system.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03130669
Contributor : Isabelle Gouat <>
Submitted on : Wednesday, February 3, 2021 - 5:33:16 PM
Last modification on : Tuesday, March 9, 2021 - 5:09:37 PM

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Bo Yang, Chao Liu, Wenfeng Zheng. PCA-based 3D Pose Modeling for Beating Heart Tracking. 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2017), Jul 2017, Guilin, China. pp.586-590, ⟨10.1109/FSKD.2017.8393335⟩. ⟨lirmm-03130669⟩

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