Spoiler alert: The answer is no, but getting to why is a trip through the nature of human creativity itself.

Neural Style Transfer is a striking, recently-developed technique that uses neural networks to artistically redraw an image in the style of a source style image. This paper explores the use of this technique in a production setting, applying Neural Style Transfer to redraw key scenes in 'Come Swim' in the style of the impressionistic painting that inspired the film. We document how the technique can be driven within the framework of an iterative creative process to achieve a desired look, and propose a mapping of the broad parameter space to a key set of creative controls. We hope that this mapping can provide insights into priorities for future research.

In surgical simulation, it is common practice to use tetrahedral meshes as models for anatomy. These meshes are versatile, and can be used with a number of different physically based modelling schemes. A variety of mesh generators are available that can automatically create tetrahedral meshes from segmented anatomical volumes. Each mesh generation scheme offers its own set of unique attributes. However, few are readily available. When choosing a mesh generator for simulation, it is critical for it to output good-quality, patient-specific meshes that provide a good approximation of the shape or volume to be modelled. To keep computation time within the bounds required for real-time interaction, there is also a limit imposed on the number of elements in the mesh generated. To the authors knowledge, there has been little work directly assessing the suitability of mesh generators for surgical simulation. This paper seeks to address this issue by assessing the use of six mesh generators in a surgical simulation scenario, and examining how they affect simulation precision. This paper aims to perform these comparisons against high-resolution reference meshes, where we examine the precision of meshes from the same mesh generator at different levels of complexity.

In surgical simulation, it is common practice to use tetrahedral meshes as models for anatomy. A variety of mesh generators can automatically create tetrahedral meshes from segmented anatomical volumes, each offering its own set of unique attributes. To the authors knowledge, there has been little work directly assessing the suitability of different mesh generation schemes for surgical simulation. This paper seeks to address this issue by assessing the use of four mesh generators in a surgical simulation scenario, and examining how they affect simulation precision. The comparisons are performed against high-resolution reference meshes, in which we propose a novel error metric for assessing the efficacy of mesh generation schemes

Cuts on deformable organs are a central task in the set of physical operations needed in many surgical simulation environments. Our BioMedIA surgical simulator structures are Finite Element Models, driven by displacements on the touched nodes as opposed to forces. This approach allows for realistic simulation of both deformation and haptic response at real-time rates. The integration of condensation into our system increases its efficiency, and allows for complex interaction on larger meshes than would normally be permitted with available memory. We present an extension of our novel algorithm for cuts in deformable organs, in the context of condensed matrices. We show results from our surgical simulation system with real-time haptic feedback.

In this paper we present a technique for the modelling of realistic collisions between arbitrary rigid surgical tools and deformable geometry that is independent of the resolution of colliding objects. We use a spatial hash table to provide an efficient narrow-phase collision detection and modelling backend. This is combined with previous work on collision modelling in our surgical simulation environment to model realistic collisions and collision response at haptic rates.

We propose a real-time procedure for performing topology modifications on finite element models of objects with linear elastic behaviour. For a 3D tetrahedral model, it requires the inversion of a 6 × 6 matrix and the weighted multiplication of a thin matrix with its transpose. We exemplify with an implementation in our surgical simulator, where we impose the tight computational constraints of haptic feedback. Our experimental results show that we can obtain response times of under one second for objects represented by tetrahedral meshes with more than 2000 nodes.

In this paper we tackle the problem of tetrahedralization by breaking non-convex polyhedra into convex subpolyhedra, tetrahedralizing these convex subpolyhedra and merging them together. We generate a Binary Space Partition (BSP) tree from the triangular faces of a polyhedron and use this to identify the convex subpolyhedra in the polyhedron. Each convex subpolyhedron is tetrahedralized individually. Using an original merging process, the boundaries between these subpolyhedra are joined and tetrahedralized, ensuring that no tetrahedra are created outside of the original polyhedron in this merging process.

This paper describes some of the considerations involved in the development of an intelligent integrated vehicle health monitoring system from a "top-down", systems perspective.