Finite Element Based Tracking of Deforming Surfaces

We present an approach to robustly track the geometry of an object that deforms over time from a set of input point clouds captured from a single viewpoint. The deformations we consider are caused by applying forces to known locations on the object's surface. Our method combines the use of prior information on the geometry of the object modeled by a smooth template and the use of a linear finite element method to predict the deformation. This allows the accurate reconstruction of both the observed and the unobserved sides of the object. We present tracking results for noisy low-quality point clouds acquired by either a stereo camera or a depth camera, and simulations with point clouds corrupted by different error terms. We show that our method is also applicable to large non-linear deformations.Comment: additional experiment

Semantic 3D Reconstruction with Finite Element Bases

We propose a novel framework for the discretisation of multi-label problems on arbitrary, continuous domains. Our work bridges the gap between general FEM discretisations, and labeling problems that arise in a variety of computer vision tasks, including for instance those derived from the generalised Potts model. Starting from the popular formulation of labeling as a convex relaxation by functional lifting, we show that FEM discretisation is valid for the most general case, where the regulariser is anisotropic and non-metric. While our findings are generic and applicable to different vision problems, we demonstrate their practical implementation in the context of semantic 3D reconstruction, where such regularisers have proved particularly beneficial. The proposed FEM approach leads to a smaller memory footprint as well as faster computation, and it constitutes a very simple way to enable variable, adaptive resolution within the same model

As-Built 3D Heritage City Modelling to Support Numerical Structural Analysis: Application to the Assessment of an Archaeological Remain

Terrestrial laser scanning is a widely used technology to digitise archaeological, architectural and cultural heritage. This allows for modelling the assets’ real condition in comparison with traditional data acquisition methods. This paper, based on the case study of the basilica in the Baelo Claudia archaeological ensemble (Tarifa, Spain), justifies the need of accurate heritage modelling against excessively simplified approaches in order to support structural safety analysis. To do this, after validating the 3Dmeshing process frompoint cloud data, the semi-automatic digital reconstitution of the basilica columns is performed. Next, a geometric analysis is conducted to calculate the structural alterations of the columns. In order to determine the structural performance, focusing both on the accuracy and suitability of the geometric models, static and modal analyses are carried out by means of the finite element method (FEM) on three different models for the most unfavourable column in terms of structural damage: (1) as-built (2) simplified and (3) ideal model without deformations. Finally, the outcomes show that the as-built modelling enhances the conservation status analysis of the 3D heritage city (in terms of realistic compliance factor values), although further automation still needs to be implemented in the modelling process

High Fidelity Bioelectric Modelling of the Implanted Cochlea

Cochlear implants are medical devices that can restore sound perception in individuals with sensorineural hearing loss (SHL). Since their inception, improvements in performance have largely been driven by advances in signal processing, but progress has plateaued for almost a decade. This suggests that there is a bottleneck at the electrode-tissue interface, which is responsible for enacting the biophysical changes that govern neuronal recruitment. Understanding this interface is difficult because the cochlea is small, intricate, and difficult to access. As such, researchers have turned to modelling techniques to provide new insights. The state-of-the-art involves calculating the electric field using a volume conduction model of the implanted cochlea and coupling it with a neural excitation model to predict the response. However, many models are unable to predict patient outcomes consistently. This thesis aims to improve the reliability of these models by creating high fidelity reconstructions of the inner ear and critically assessing the validity of the underlying and hitherto untested assumptions. Regarding boundary conditions, the evidence suggests that the unmodelled monopolar return path should be accounted for, perhaps by applying a voltage offset at a boundary surface. Regarding vasculature, the models show that large modiolar vessels like the vein of the scala tympani have a strong local effect near the stimulating electrode. Finally, it appears that the oft-cited quasi-static assumption is not valid due to the high permittivity of neural tissue. It is hoped that the study improves the trustworthiness of all bioelectric models of the cochlea, either by validating the claims of existing models, or by prompting improvements in future work. Developing our understanding of the underlying physics will pave the way for advancing future electrode array designs as well as patient-specific simulations, ultimately improving the quality of life for those with SHL

Full-field vibrometry by high-speed digital holography for middle-ear mechanics

Hearing loss affects approximately 1 in 10 people in the world and this percentage is increasing every year. Some of the most common causes of hearing loss are disorders of the middle-ear. Early detection and diagnosis of hearing loss as well as research to understand the hearing processes depend on medical and research tools for quantification of hearing capabilities and the function of the middle-ear in the complex acousto-mechanical transformation of environmental sounds into vibrations of the middle-ear, particular of the human tympanic membrane (TM or eardrum). Current ear exams assess the state of a patient’s hearing capabilities mainly based on qualitative evaluation of the healthiness of the TM. Existing quantitative clinical methods for description of the motion of the TM are limited to either average acoustic estimates (admittance or reflectance) or single-point displacement measurements. Such methods could leave examiners and researchers blind to the complex spatio-temporal response of the nanometer scale displacements of the entire TM. Current state-of-the-art medical research tools provide full-field nanometer displacement measurements of the surface of the human TM excited by steady state (tonal) stimuli. However, to fully understand the mechanics of hearing, and the complex acousto-mechanical characteristics of TM in particular, new tools are needed for full-field high-speed characterization of the nanometer scale displacements of the human TM subjected to impulse (wideband) acoustic excitation. This Dissertation reports the development of a new high-speed holographic system (HHS) for full-field nanometer transient (i.e., \u3e 10 kHz) displacement measurement of the human middle-ear and the tympanic membrane, in particular. The HHS allows spatial (i.e., \u3e500k data points) and temporal (i.e., \u3e 40 kHz) resolutions that enable the study of the acoustical and mechanical characteristics of the middle-ear at a level of detail that have never been reached before. The realization of the HHS includes the development and implementation of novel phase sampling and acquisition approaches that allow the use of state-of-the-art high-resolution (i.e., \u3e5 MP) and high-speed (\u3e 80,000 fps) cameras through modular and expandable control architectures. The development of novel acquisition approaches allows the use of conventional speed (i.e., \u3c20 fps) cameras to realize high-temporal resolutions (i.e., \u3c15 us) at equivalent sampling rates of \u3e 50,000 fps with minimum hardware cost and modifications. The design and implementation of novel spatio-temporal phase sampling methods utilize the high temporal resolution (i.e., \u3c 5 us exposure) and frame rate (i.e., \u3e80,000 fps) of high-speed cameras without imposing constraints on their spatial resolution (i.e., \u3e20 um pixel size). Additionally, the research and in-vivo applications capabilities of the HHS are extended through the development and implementation of a holographic otoscope head (OH) and a mechatronic otoscope positioner (MOP). The large (i.e., \u3e 1 GB with \u3e 8x10^9 parameters) spatio-temporal data sets of the HHS measurements are automatically processed by custom parallel data mining and interpretation (PDMI) methods, which allow automatic quantification of medically relevant motion parameters (MRMPs), such as modal frequencies, time constants, and acoustic delays. Such capabilities could allow inferring local material properties across the surface of the TM. The HHS is a new medical tool that enables otologists to improve the quality of diagnosis and treatments as well as provides researchers with spatio-temporal information of the hearing process at a level of detail never reached before

Single View Augmentation of 3D Elastic Objects

International audienceThis paper proposes an efficient method to capture and augment highly elastic objects from a single view. 3D shape recovery from a monocular video sequence is an underconstrained problem and many approaches have been proposed to enforce constraints and resolve the ambiguities. State-of-the art solutions enforce smoothness or geometric constraints, consider specific deformation properties such as inextensibility or ressort to shading constraints. However, few of them can handle properly large elastic deformations. We propose in this paper a real-time method which makes use of a me chanical model and is able to handle highly elastic objects. Our method is formulated as a energy minimization problem accounting for a non-linear elastic model constrained by external image points acquired from a monocular camera. This method prevents us from formulating restrictive assumptions and specific constraint terms in the minimization. The only parameter involved in the method is the Young's modulus where we show in experiments that a rough estimate of its value is sufficient to obtain a good reconstruction. Our method is compared to existing techniques with experiments conducted on computer-generated and real data that show the effectiveness of our approach. Experiments in the context of minimally invasive liver surgery are also provided