PCA-based 3D Pose Modeling for Beating Heart Tracking - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2018

PCA-based 3D Pose Modeling for Beating Heart Tracking

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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lirmm-03130669 , version 1 (03-02-2021)

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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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