We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: An intrinsic spectral matching pipeline, a morphable model, and an extrinsic details refinement. By operating in conjunction, these tools allow us to greatly improve the quality of the matching while at the same time resolving the key issues exhibited by each tool individually. In this paper we present an innovative High-Resolution Augmentation (HRA) strategy that enables highly accurate correspondence even in the presence of significant mesh resolution mismatch between the input shapes. This augmentation provides an effective workaround for the resolution limitations imposed by the adopted morphable model. The HRA in its global and localized versions represents a novel refinement strategy for surface subdivision methods. We demonstrate the accuracy of the proposed pipeline on multiple challenging benchmarks, and showcase its effectiveness in surface registration and texture transfer.

Marin, R., Melzi, S., Rodola, E., Castellani, U. (2019). High-resolution augmentation for automatic template-based matching of human models. In Proceedings - 2019 International Conference on 3D Vision. 3DV 2019 (pp.230-239). Institute of Electrical and Electronics Engineers Inc. [10.1109/3DV.2019.00034].

High-resolution augmentation for automatic template-based matching of human models

Melzi S;
2019

Abstract

We propose a new approach for 3D shape matching of deformable human shapes. Our approach is based on the joint adoption of three different tools: An intrinsic spectral matching pipeline, a morphable model, and an extrinsic details refinement. By operating in conjunction, these tools allow us to greatly improve the quality of the matching while at the same time resolving the key issues exhibited by each tool individually. In this paper we present an innovative High-Resolution Augmentation (HRA) strategy that enables highly accurate correspondence even in the presence of significant mesh resolution mismatch between the input shapes. This augmentation provides an effective workaround for the resolution limitations imposed by the adopted morphable model. The HRA in its global and localized versions represents a novel refinement strategy for surface subdivision methods. We demonstrate the accuracy of the proposed pipeline on multiple challenging benchmarks, and showcase its effectiveness in surface registration and texture transfer.
No
paper
Geometry processing; High Resolution; Morphable Model; Registration;
English
7th International Conference on 3D Vision, 3DV 2019
978-1-7281-3131-3
Marin, R., Melzi, S., Rodola, E., Castellani, U. (2019). High-resolution augmentation for automatic template-based matching of human models. In Proceedings - 2019 International Conference on 3D Vision. 3DV 2019 (pp.230-239). Institute of Electrical and Electronics Engineers Inc. [10.1109/3DV.2019.00034].
Marin, R; Melzi, S; Rodola, E; Castellani, U
File in questo prodotto:
File Dimensione Formato  
Marin_High-Resolution_2019.pdf

Solo gestori archivio

Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Dimensione 2.01 MB
Formato Adobe PDF
2.01 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/350434
Citazioni
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
Social impact