138,851 research outputs found
Intrinsic Dynamic Shape Prior for Fast, Sequential and Dense Non-Rigid Structure from Motion with Detection of Temporally-Disjoint Rigidity
While dense non-rigid structure from motion (NRSfM) has been extensively studied from the perspective of the reconstructability problem over the recent years, almost no attempts have been undertaken to bring it into the practical realm. The reasons for the slow dissemination are the severe ill-posedness, high sensitivity to motion and deformation cues and the difficulty to obtain reliable point tracks in the vast majority of practical scenarios. To fill this gap, we propose a hybrid approach that extracts prior shape knowledge from an input sequence with NRSfM and uses it as a dynamic shape prior for sequential surface recovery in scenarios with recurrence. Our Dynamic Shape Prior Reconstruction (DSPR) method can be combined with existing dense NRSfM techniques while its energy functional is optimised with stochastic gradient descent at real-time rates for new incoming point tracks. The proposed versatile framework with a new core NRSfM approach outperforms several other methods in the ability to handle inaccurate and noisy point tracks, provided we have access to a representative (in terms of the deformation variety) image sequence. Comprehensive experiments highlight convergence properties and the accuracy of DSPR under different disturbing effects. We also perform a joint study of tracking and reconstruction and show applications to shape compression and heart reconstruction under occlusions. We achieve state-of-the-art metrics (accuracy and compression ratios) in different scenarios
Micro computed tomography based finite element models of calcium phosphate scaffolds for bone tissue engineering
Bone is a living tissue that is able to regenerate by itself. However, when severe bone defects occur, the natural regeneration may be impaired. In these cases, bone graft substitutes can be used to induce the natural healing process. As a scaffold for tissue engineering, these bone graft substitutes have to meet specific requirements. Among others, the material must be biocompatible, biodegradable and have a porous structure to allow vascularization, cell migration and formation of new bone. Additionally, the mechanical properties of the scaffold have to resemble the ones of native tissue. The goal of this project is to create a computational model of the calcium phosphate scaffolds that are produced by rapid-prototyping by the Biomaterials, Biomechanics, and Tissue Engineering group at the Technical University of Catalonia. These models are based on finite element analysis and micro computed tomography images in order to consider the actual architecture of the scaffolds. The generated FE-models allow the computation of both local strains, which act as mechanical stimuli on attached cells, as well as the behaviour of the entire scaffold. When considering this information, the scaffold can be optimized for tissue differentiation by tuning both the scaffold architecture and the scaffold material bulk properties.Incomin
Learning quadrangulated patches for 3D shape parameterization and completion
We propose a novel 3D shape parameterization by surface patches, that are
oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail
on local patches, we learn a patch dictionary that identifies principal surface
features of the shape. Unlike previous methods, we are able to encode surface
patches of variable size as determined by the user. We propose novel methods
for dictionary learning and patch reconstruction based on the query of a noisy
input patch with holes. We evaluate the patch dictionary towards various
applications in 3D shape inpainting, denoising and compression. Our method is
able to predict missing vertices and inpaint moderately sized holes. We
demonstrate a complete pipeline for reconstructing the 3D mesh from the patch
encoding. We validate our shape parameterization and reconstruction methods on
both synthetic shapes and real world scans. We show that our patch dictionary
performs successful shape completion of complicated surface textures.Comment: To be presented at International Conference on 3D Vision 2017, 201
Roadmap to the morphological instabilities of a stretched twisted ribbon
We address the mechanics of an elastic ribbon subjected to twist and tensile
load. Motivated by the classical work of Green and a recent experiment that
discovered a plethora of morphological instabilities, we introduce a
comprehensive theoretical framework through which we construct a 4D phase
diagram of this basic system, spanned by the exerted twist and tension, as well
as the thickness and length of the ribbon. Different types of instabilities
appear in various "corners" of this 4D parameter space, and are addressed
through distinct types of asymptotic methods. Our theory employs three
instruments, whose concerted implementation is necessary to provide an
exhaustive study of the various parameter regimes: (i) a covariant form of the
F\"oppl-von K\'arm\'an (cFvK) equations to the helicoidal state - necessary to
account for the large deflection of the highly-symmetric helicoidal shape from
planarity, and the buckling instability of the ribbon in the transverse
direction; (ii) a far from threshold (FT) analysis - which describes a state in
which a longitudinally-wrinkled zone expands throughout the ribbon and allows
it to retain a helicoidal shape with negligible compression; (iii) finally, we
introduce an asymptotic isometry equation that characterizes the energetic
competition between various types of states through which a twisted ribbon
becomes strainless in the singular limit of zero thickness and no tension.Comment: Submitted to Journal of Elasticity, themed issue on ribbons and
M\"obius band
Compression for Smooth Shape Analysis
Most 3D shape analysis methods use triangular meshes to discretize both the
shape and functions on it as piecewise linear functions. With this
representation, shape analysis requires fine meshes to represent smooth shapes
and geometric operators like normals, curvatures, or Laplace-Beltrami
eigenfunctions at large computational and memory costs.
We avoid this bottleneck with a compression technique that represents a
smooth shape as subdivision surfaces and exploits the subdivision scheme to
parametrize smooth functions on that shape with a few control parameters. This
compression does not affect the accuracy of the Laplace-Beltrami operator and
its eigenfunctions and allow us to compute shape descriptors and shape
matchings at an accuracy comparable to triangular meshes but a fraction of the
computational cost.
Our framework can also compress surfaces represented by point clouds to do
shape analysis of 3D scanning data
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