Non-rigid 3D Shape Registration using an Adaptive Template

Research output: Contribution to conferencePaperpeer-review


We present a new fully-automatic non-rigid 3D shape registration (morphing) framework comprising (1) a new 3D landmarking and pose normalisation method; (2) an adaptive shape template method to improve the convergence of registration algorithms and achieve a better final shape correspondence and (3) a new iterative registration method that combines Iterative Closest Points with Coherent Point Drift (CPD) to achieve a more stable and accurate correspondence establishment than standard CPD. We call this new morphing approach \emph{Iterative Coherent Point Drift} (ICPD). Our proposed framework is evaluated qualitatively and quantitatively on three datasets: Headspace, BU3D and a synthetic LSFM dataset, and is compared with several other methods. The proposed framework is shown to give state-of-the-art performance.
Original languageEnglish
Number of pages15
Publication statusPublished - 14 Sep 2018
EventECCV 2018: PeopleCap Workshop - GASTEIG Cultural Center, Munich, Germany
Duration: 14 Sep 201814 Sep 2018


WorkshopECCV 2018: PeopleCap Workshop
Internet address


  • 3D registration; 3D shape morphing; 3D morphable models

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