Mark W. Jones

• PhD, Computer Graphics and Visualization
• Professor at Swansea University

We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders to create an efficient feature representation for image tiles derived from remote sensing satel...

Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Ove...

Recent achievements of sequence prediction models in numerous domains, including compression, provide great potential for novel learning-based codecs. In such models, the input sequence’s shape and size play a crucial role in learning the mapping function of the data distribution to the target output. This work examines numerous input configuration...

We present a comprehensive, detailed review of time-series data analysis, with emphasis on deep time-series clustering (DTSC), and a case study in the context of movement behavior clustering utilizing the deep clustering method. Specifically, we modified the DCAE architectures to suit time-series data at the time of our prior deep clustering work....

Deep networks often possess a vast number of parameters, and their significant redundancy in parameterization has become a widely-recognized property. This presents significant challenges and restricts many deep learning applications, making the focus on reducing the complexity of models while maintaining their powerful performance. In this paper,...

The objective of this work was to investigate from a user perspective linkage between a 1D time-series view of data and a 2D representation provided by dimension reduction techniques. Our hypothesis is that when such interaction happens seamlessly, the use of these linked views, compared to only interacting with the 1D time-series view, for the ubi...

The achievement of convolutional neural networks (CNNs) in a variety of applications is accompanied by a dramatic increase in computational costs and memory requirements. In this paper, we propose a novel framework to measure the importance of individual hidden units by computing a measure of relevance to identify the most critical filters and prun...

Visual analytics for time series data has received a considerable amount of attention. Different approaches have been developed to understand the characteristics of the data and obtain meaningful statistics in order to explore the underlying processes, identify and estimate trends, make decisions and predict the future. The machine learning and vis...

Deep convolutional auto-encoder (DCAE) allows to obtain useful features via its internal layer and provide an abstracted latent representation, which has been exploited for clustering analysis. DCAE allows a deep clustering method to extract similar patterns in lower-dimensional representation and find idealistic representative centers for distribu...

The consistent alignment of point clouds obtained from multiple scanning positions is a crucial step for many 3D modeling systems. This is especially true for environment modeling. In order to observe the full scene, a common approach is to rotate the scanning device around a rotation axis using a turntable. The final alignment of each frame data c...

There is a need for solutions which assist users to understand long time-series data by observing its changes over time, finding repeated patterns, detecting outliers, and effectively labeling data instances. Although these tasks are quite distinct and are usually tackled separately, we present an interactive visual analytics system and approach th...

A fully-parallelized work-time optimal algorithm is presented for computing the exact Euclidean Distance Transform (EDT) of a 2D binary image with the size of n × n. Unlike existing PRAM (Parallel Random Access Machine) and other algorithms, this algorithm is suitable for implementation on modern SIMD (Single Instruction Multiple Data) architecture...

Urban areas are now the dominant human habitat, with more influence than ever on economies, environment and our health. Dynamic urban models are increasingly applied to explore possible future scenarios of urban development to achieve sustainability. However, it is still challenging to use these models for prediction, taking into consideration the...

Evaluating image quality in Monte Carlo rendered images is an important aspect of the rendering process as we often need to determine the relative quality between images computed using different algorithms and with varying amounts of computation. The use of a gold-standard, reference image, or ground truth is a common method to provide a baseline w...

In this paper, we introduce a framework for implementing deep copy on top of MPI. The process is initiated by passing just the root object of the dynamic data structure. Our framework takes care of all pointer traversal, communication, copying and reconstruction on receiving nodes. The benefit of our approach is that MPI users can deep copy complex...

Background We are increasingly using recording devices with multiple sensors operating at high frequencies to produce large volumes of data which are problematic to interpret. A particularly challenging example comes from studies on animals and humans where researchers use animal-attached accelerometers on moving subjects to attempt to quantify beh...

Background: Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information. Des...

Collecting sensor data results in large temporal data sets which need to be visualized, analyzed, and presented. Onedimensional time-series charts are used, but these present problems when screen resolution is small in comparison to the data. This can result in severe over-plotting, giving rise for the requirement to provide effective rendering and...

Background Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information. Descr...

Background Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively preclud...

Understanding the way humans inform themselves about their environment is pivotal in helping explain our susceptibility to stimuli and how this modulates behaviour and movement patterns. We present a new device, the Human Interfaced Personal Observation Platform (HIPOP), which is a head-mounted (typically on a hat) unit that logs magnetometry and a...

Biologists studying animals in their natural environment are increasingly using sensors such as accelerometers in animal-attached ‘smart’ tags because it is widely acknowledged that this approach can enhance the understanding of ecological and behavioural processes. The potential of such tags is tempered by the difficulty of extracting animal behav...

In association with Urban modelers, we have created DynaMoVis, a system for the visualization of dynamic models. The prediction of the evolution of urban and ecological systems is difficult because they are complex nonlinear systems that exhibit self-organization, emergence, and path dependence. Without a good understanding of the dynamics, interve...

Hyperspectral image visualization reduces color bands to three, but prevailing linear methods fail to address data characteristics, and nonlinear embeddings are computationally demanding. Qualitative evaluation of embedding is also lacking. We propose faithful stochastic proximity embedding (FSPE), which is a scalable and nonlinear dimensionality r...

In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales...

We present a visualization tool aimed specifically at the development and optimization of photon map denoising methods. Our tool allows the rapid testing of hypotheses and algorithms through the use of parallel coordinates, domain-specific scripting, colour mapping and point plots. Interaction is carried out by brushing, adjusting parameters and fo...

Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently cha...

Stream compaction is an important parallel computing primitive that produces a reduced (compacted) output stream consisting of only valid elements from an input stream containing both invalid and valid elements. Computing on this compacted stream rather than the mixed input stream leads to improvements in performance, load balancing and memory foot...

Streamline seeding rakes are widely used in vector field visualization. We present new approaches for calculating similarity between integral curves (streamlines and pathlines). While others have used similarity distance measures, the computational expense involved with existing techniques is relatively high due to the vast number of euclidean dist...

Noise removal for Monte Carlo global illumination rendering is a well known problem, and has seen significant attention from image-based filtering methods. However, many state of the art methods breakdown in the presence of high frequency features, complex lighting and materials. In this work we present a probabilistic image based noise removal and...

Visual computing represents one of the most challenging and inspiring arenas in computer science. Today, fifty percent of content on the internet is in the form of visual data and information, and more than fifty percent of the neurons in the human brain are used in visual perception and reasoning. RIVIC is the collaborative amalgamation of researc...

This paper presents a novel approach to detecting and preserving fine illumination structure within photon maps. Data derived from each photon's primal trajectory is encoded and used to build a high-dimensional kd-tree. Incorporation of these new parameters allows for precise differentiation between intersecting ray envelopes, thus minimizing detai...

We introduce a novel algorithm for progressively removing noise from view-independent photon maps while simultaneously minimizing residual bias. Our method refines a primal set of photons using data from multiple successive passes to estimate the incident flux local to each photon. We show how this information can be used to guide a relaxation step...

In this paper, we seek to eliminate the noise caused by caustic paths during progressive Monte Carlo path tracing. We employ a filtering strategy over path space, handling each subspace using specialized derivations of path tracing and progressive photon mapping. Evaluating diffuse paths with path tracing allows the use of sample stratification ove...

Today real-time sports performance analysis is a crucial aspect of matches in many major sports. For example, in soccer and rugby, team analysts may annotate videos during the matches by tagging specific actions and events, which typically result in some summary statistics and a large spreadsheet of recorded actions and events. To a coach, the summ...

Parallel coordinates is one of the most popular and widely used visualization techniques for large, high dimensional data. Often, data attributes are visualized on individual axes with polylines joining them. However, some data attributes are more naturally represented with a spherical coordinate system. We present a novel coupling of parallel coor...

In this paper, we present a new visual way of exploring state sequences in large observational time-series. A key advantage of our method is that it can directly visualize higher-order state transitions. A standard first order state transition is a sequence of two states that are linked by a transition. A higher-order state transition is a sequence...

A new area of biological research is identifying and grouping patterns of behaviour in wild animals by analysing data obtained through the attachment of tri-axial accelerometers. As these recording devices become smaller and less expensive their use has increased. Currently acceleration data are visualised as 2D time series plots, and analyses are...

The photon mapping method is one of the most popular algorithms employed in computer graphics today. However, obtaining good results is dependent on several variables including kernel shape and bandwidth, as well as the properties of the initial photon distribution. While the photon density estimation problem has been the target of extensive resear...

Photon mapping is an efficient method for producing high-quality, photorealistic images with full global illumination. In this paper we present a more accurate and efficient approach to final gathering using the photon map based upon hierarchical evaluation of the photons over each surface. We use the footprint of each gather ray to calculate the i...

A sampled object representation (SOR) defines a graphical model using data obtained from a sampling process, which takes a collection of samples at discrete positions in space in order to capture certain geometrical and physical properties of one or more objects of interest. Examples of SORs include images, videos, volume datasets and point dataset...

We present a rendering algorithm for the forward projection of volume deformations. Spatial deformations are modeled by allowing the user to define curve skeletons inside the target object. Our rendering method utilises modern consumer graphics hardware and is integrated into an easy to use interface. In addition, we give an analysis of spatial tra...

Recent hardware and software advances have demonstrated that it is now practicable to run large visual computing tasks over heterogeneous hardware with output on multiple types of display devices. As the complexity of the enabling infrastructure increases, then so too do the demands upon the programmer for task integration as well as the demands up...

A distance field is a representation where, at each point within the field, we know the distance from that point to the closest point on any object within the domain. In addition to distance, other properties may be derived from the distance field, such as the direction to the surface, and when the distance field is signed, we may also determine if...

We introduce a new framework for non-linear, non-reconstructive deformation of volumetric datasets. Traditional techniques for deforming volumetric datasets non-linearly usually involve a reconstruction stage, where a new deformed volume is recon-structed and then sent to the renderer. Our intuitive sweep-based technique avoids the drawbacks of rec...

This paper describes a flexible visualization architecture based on software agents, which enables the abstraction and reuse of rendering strategies. Using a reification of the rendering environment, the system is able to add new rendering strategies (such as distributed rendering or progressive rendering) to an existing pipeline, without any modif...

Texture mapping is an extremely powerful and flexible tool for adding complex surface detail to an object. This paper introduces a method of surface texturing and hypertexturing complex volumetric objects in real-time. We employ distance field volume representations, texture based volume rendering and procedural texturing techniques with Shader Mod...

If we were to have a Grid infrastructure for visualization, what technologies would be needed to build such an infrastructure, what kind of applications would benefit from it, and what challenges are we facing in order to accomplish this goal? In this survey paper, we make use of the term 'visual supercomputing' to encapsulate a subject domain conc...

A discretely sampled object representation (DSOR) denes a graphical model using data obtained by a sampling process, which takes a collection of samples at discrete positions in space in order to capture certain geometrical and physical properties of one or more objects of interest. Examples of DSORs include images, videos, volume datasets and poin...

This paper compares various techniques for compressing floating point distance fields. Both lossless and lossy techniques are compared against a new lossless technique. The new Vector Transform technique creates a predictor based upon a Vector Distance Transform and its suitability for distance field data sets is reported. The new technique produce...

This paper describes a fully interactive modelling system, which we have called ClayWorks, for defining the implicit geometry of 3D objects using parametric base primitives and deformations. The goal of this system is to provide a means for describing object data and its creation history by using a series of parametric steps that can be modified po...

This paper describes a technique for producing realistic animations of melting objects. The work presented here introduces a method that accurately models both thermal flow and the latent heat during the phase change. The mechanism for energy transfer to the model is via both boundary conditions and radiation. Emphasis is made on accurately modelli...

This paper will examine hyper-texture rendering techniques and will demonstrate how Volume data sets may be adapted in order for hypertexture to be applied. Details are given of a process for the conversion of complex objects. such as CT scans, into accurate distance fields. Hypertexture is applied to these objects and example renderings include th...

In this paper we demonstrate computer aided techniques in the area of the reconstruction of facial features from skeletal remains. We outline the desired features of a system for skull identification, and demonstrate our progress in the area which builds upon our previous work on distance fields for volumetric data. In addition to the application w...

This paper presents the design and implementation of artistic effects in modelling and rendering of volume datasets. Following different stages of a volume-based graphics pipeline, we examine various properties of volume data, and illustrate how expressive and non-photorealistic effects can be implemented. We demonstrate that the true 3D nature of...

This paper will examine the current chamfer and vector distance transforms for encoding objects as distance fields. A new vector distance transform is introduced which uses the city-block chamfer distance transform as a basis. Detailed error analysis using real CT data is presented, demonstrating the improved accuracy of the new approach over exist...

Voxelisation is the process of converting a source object of any data type into a three-dimensional grid of voxel values. This voxel grid should represent the original object as closely as possible, although some inaccuracies will occur due to the discrete nature of the voxel grid representation. In this paper we report our ongoing research into me...

This paper presents the design and implementation of artistic effects in modelling and rendering of volume datasets. Following different stages of a volume-based graphics pipeline, we examine various properties of volume data, and illustrate how expressive and non-photorealistic effects can be implemented. We demonstrate that the true 3D nature of...

Abstract Distance fields are a widely investigated area within the area of Vol - ume Graphics Research is divided between applications; such as - skeletonisa - tion, hypertexture, voxelisation, acceleration of rendering techniques, correlation and collision detection; and the fundamental algorithmic calculation of the dis - tance fields This paper...

Distance fields are a widely investigated area within the area of Vol-ume Graphics. Research is divided between applications; such as – skeletonisa-tion, hypertexture, voxelisation, acceleration of rendering techniques, correlation and collision detection; and the fundamental algorithmic calculation of the dis-tance fields. This paper concentrates...

Distance fields are a two-or three-dimensional array of values, where each value is the minimum distance to the encoded object. Usually distance fields are signed, such that negative values signify the point is inside the object, and positive are outside. Distance fields are be-coming a popular research area as more applications are discovered, and...

Voxelisation is the term given to the process of converting data from one source type into a three dimensional volume of data values. The tech- niques known collectively as volume visualisa- tion can then be applied to the data in order to produce a graphical representation of the object. This paper gives a new practical approach to the voxelisatio...

The increasing use of computer-generated graphical representations of everyday objects, in both entertainment and industry (including such areas as medical imaging), has led to the development of powerful rendering tools such as ray tracing, radiosity and volume rendering (see [1, 2] for a description). However, the images produced by such applicat...

The problem of creating a sequence of inbetween volumes smoothly transforming from one given volume to another is referred to as volume metamorphosis or volume morphing. Several methods that provide the solution to the problem are described and compared in this paper. Tests have shown that some of these methods are capable of produce good quality m...

Genetic algorithms are proposed as a method for creating objects within the volume graphics environment. An approach to the realistic rendering of general volume data is given in the paper, along with example renderings of scanned and genetically produced volume graphic objects. The rendering method is demonstrated by rendering complex implicitly d...

Research into volume graphics have lead us to new methods for the vox- elisation of meshes and the ultra high quality rendering of volumetric data. Recently it has been reported by us (1) that our method of voxelisation and subsequent rendering can produce images faster than traditional ray tracing methods. In this paper we present in detail the Di...

Voxelisation is the term given to the process of converting data from one source type into a three dimensional volume of data values. The techniques known collectively as volume visualisation can then be applied to the data in order to produce a graphical representation of the object. This paper gives a practical approach to the voxelisation of dat...

The rapid development of volume graphics offers ample scope to develop new methods and tools for computer graphics and visualization. This paper is concerned with methods for specifying and controlling complex transformations of volumetric data. A volume distortion algorithm is presented, which allows one volume to be distorted into another under t...

In this technical report, two different methods for calculating the distance between a point and a triangle in 3D space will be described. It will be shown that it is far more efficient to calculate the distance by using a rotation to make the problem 2D. Both methods are tested with relation to the production of 3D data from polygonal meshes (voxe...

This paper presents a new approach to the construction of a surface from a stack of contour slices. Unlike most existing methods, this new approach handles ambiguous conditions consistently without employing an algorithm to establish a correspondence between vertices on one contour and those on the next. It is easy to implement and fast to compute,...

Visualization of 3D, unsteady (4D) flow is very difficult due to both perceptual challenges and the large size of 4D vector field data. Here, we describe the use of integral surfaces for visualization of CFD simulation data. By "integral" surfaces we mean surfaces based on massless particles that are integrated according to the underlying flow. Tra...