Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

Parametric CAD model based shape optimization using adjoint functions

Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.

Characterisation of polyethylene powders for rotational moulding and effect of powder size and shape on densification behaviour

The particle size, shape and distribution of a range of rotational moulding polyethylenes (PEs) ground to powder was investigated using a novel visual data acquisition and analysis system (TP Picture®), developed by Total Petrochemicals. Differences in the individual particle shape factors of the powder samples were observed and correlations with the grinding conditions were determined. When heated, the bubble dissolution behaviour of the same powders was investigated and the shape factor correlated with densification rate, bubble size and bubble distribution.

Working with Students to Shape Library Services at The Hive

The Hive represents a completely new vision for libraries and, since opening in 2012, has helped us constantly review and change our approach to service delivery. Our most recent work is around student engagement, where we are changing our relationship with students moving from passive recipients of services to active participants in service design, evaluation and delivery. This presentation will cover some examples of our student engagement work, the benefits it brings and some of the challenges that we face.

Shape-based compliance control for snake robots

I serpenti robot sono una classe di meccanismi iper-ridondanti che appartiene alla robotica modulare. Grazie alla loro forma snella ed allungata e all'alto grado di ridondanza possono muoversi in ambienti complessi con elevata agilità. L'abilità di spostarsi, manipolare e adattarsi efficientemente ad una grande varietà di terreni li rende ideali per diverse applicazioni, come ad esempio attività di ricerca e soccorso, ispezione o ricognizione. I robot serpenti si muovono nello spazio modificando la propria forma, senza necessità di ulteriori dispositivi quali ruote od arti. Tali deformazioni, che consistono in movimenti ondulatori ciclici che generano uno spostamento dell'intero meccanismo, vengono definiti andature. La maggior parte di esse sono ispirate al mondo naturale, come lo strisciamento, il movimento laterale o il movimento a concertina, mentre altre sono create per applicazioni specifiche, come il rotolamento o l'arrampicamento. Un serpente robot con molti gradi di libertà deve essere capace di coordinare i propri giunti e reagire ad ostacoli in tempo reale per riuscire a muoversi efficacemente in ambienti complessi o non strutturati. Inoltre, aumentare la semplicità e ridurre il numero di controllori necessari alla locomozione alleggerise una struttura di controllo che potrebbe richiedere complessità per ulteriori attività specifiche. L'obiettivo di questa tesi è ottenere un comportamento autonomo cedevole che si adatti alla conformazione dell'ambiente in cui il robot si sta spostando, accrescendo le capacità di locomozione del serpente robot. Sfruttando la cedevolezza intrinseca del serpente robot utilizzato in questo lavoro, il SEA Snake, e utilizzando un controllo che combina cedevolezza attiva ad una struttura di coordinazione che ammette una decentralizzazione variabile del robot, si dimostra come tre andature possano essere modificate per ottenere una locomozione efficiente in ambienti complessi non noti a priori o non modellabili.

A three dimensional finite volume approach to the thermo-mechanical modelling of the shape casting of metals

This paper presents a three dimensional, thermos-mechanical modelling approach to the cooling and solidification phases associated with the shape casting of metals ei. Die, sand and investment casting. Novel vortex-based Finite Volume (FV) methods are described and employed with regard to the small strain, non-linear Computational Solid Mechanics (CSM) capabilities required to model shape casting. The CSM capabilities include the non-linear material phenomena of creep and thermo-elasto-visco-plasticity at high temperatures and thermo-elasto-visco-plasticity at low temperatures and also multi body deformable contact with which can occur between the metal casting of the mould. The vortex-based FV methods, which can be readily applied to unstructured meshes, are included within a comprehensive FV modelling framework, PHYSICA. The additional heat transfer, by conduction and convection, filling, porosity and solidification algorithms existing within PHYSICA for the complete modelling of all shape casting process employ cell-centred FV methods. The termo-mechanical coupling is performed in a staggered incremental fashion, which addresses the possible gap formation between the component and the mould, and is ultimately validated against a variety of shape casting benchmarks.

Computational modelling of interacting phenomena in the shape casting process

Abstract not available

Multilevel mesh partitioning for optimising domain shape

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut-edge weight in the graph with the aim of minimising the parallel communication overhead. However it has been shown that for certain classes of problem, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. In this paper therefore, we modify the multilevel algorithms in order to optimise a cost function based on aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.

Validity of shape memory NiTi colon ring BioDynamix ColonRing™ (or NiTi CAR 27™) to prevent anastomotic colorectal strictures. Preliminary results

Purpose. Anastomotic strictures occur in 3-30% of colorectal anastomosis and one of the main causes may be a reaction to the presence of the metal staples used for suturing. The aim of this study was to evaluate the efficacy of a compression anastomosis ring using the memoryshaped device in initial, i.e. nickel-titanium alloy (NiTi) for the prevention of colorectal anastomotic strictures. Patients and methods. A compression anastomosis ring device (NiTi CAR 27™) was used to perform compression anastomosis in 20 patients underwent left hemicolectomy and anterior resection of the rectum for carcinoma. An endoscopic check of the anastomosis was carried out at one month and at six months after surgery. Results. In 2 patients (10%) a dehiscence of the anastomosis occurred on the fifth and the eighth postoperative day. No anastomotic strictures were observed in any of the other 18 patients at six months follow-up after surgery. Conclusion. Our preliminary results suggest that the use of a compression anastomosis ring might well be a valid method of preventing anastomotic strictures in colorectal surgery. Further studies involving a larger number of patients are needed in order to confirm these preliminary results.

Does countershading contribute to visual camouflage by concealing 3D shape?

This is an abstract of an invited talk presented at AVA Animal Vision Meeting / Camocon 2015, which took place in Liverpool, 23 August 2015.