Modelling and Visualisation of the Optical Properties of Cloth

Cloth and garment visualisations are widely used in fashion and interior design, entertaining, automotive and nautical industry and are indispensable elements of visual communication. Modern appearance models attempt to offer a complete solution for the visualisation of complex cloth properties. In the review part of the chapter, advanced methods that enable visualisation at micron resolution, methods used in three-dimensional (3D) visualisation workflow and methods used for research purposes are presented. Within the review, those methods offering a comprehensive approach and experiments on explicit clothes attributes that present specific optical phenomenon are analysed. The review of appearance models includes surface and image-based models, volumetric and explicit models. Each group is presented with the representative authors’ research group and the application and limitations of the methods. In the final part of the chapter, the visualisation of cloth specularity and porosity with an uneven surface is studied. The study and visualisation was performed using image data obtained with photography. The acquisition of structure information on a large scale namely enables the recording of structure irregularities that are very common on historical textiles, laces and also on artistic and experimental pieces of cloth. The contribution ends with the presentation of cloth visualised with the use of specular and alpha maps, which is the result of the image processing workflow

Visual Prototyping of Cloth

Realistic visualization of cloth has many applications in computer graphics. An ongoing research problem is how to best represent and capture appearance models of cloth, especially when considering computer aided design of cloth. Previous methods can be used to produce highly realistic images, however, possibilities for cloth-editing are either restricted or require the measurement of large material databases to capture all variations of cloth samples. We propose a pipeline for designing the appearance of cloth directly based on those elements that can be changed within the production process. These are optical properties of fibers, geometrical properties of yarns and compositional elements such as weave patterns. We introduce a geometric yarn model, integrating state-of-the-art textile research. We further present an approach to reverse engineer cloth and estimate parameters for a procedural cloth model from single images. This includes the automatic estimation of yarn paths, yarn widths, their variation and a weave pattern. We demonstrate that we are able to match the appearance of original cloth samples in an input photograph for several examples. Parameters of our model are fully editable, enabling intuitive appearance design. Unfortunately, such explicit fiber-based models can only be used to render small cloth samples, due to large storage requirements. Recently, bidirectional texture functions (BTFs) have become popular for efficient photo-realistic rendering of materials. We present a rendering approach combining the strength of a procedural model of micro-geometry with the efficiency of BTFs. We propose a method for the computation of synthetic BTFs using Monte Carlo path tracing of micro-geometry. We observe that BTFs usually consist of many similar apparent bidirectional reflectance distribution functions (ABRDFs). By exploiting structural self-similarity, we can reduce rendering times by one order of magnitude. This is done in a process we call non-local image reconstruction, which has been inspired by non-local means filtering. Our results indicate that synthesizing BTFs is highly practical and may currently only take a few minutes for small BTFs. We finally propose a novel and general approach to physically accurate rendering of large cloth samples. By using a statistical volumetric model, approximating the distribution of yarn fibers, a prohibitively costly, explicit geometric representation is avoided. As a result, accurate rendering of even large pieces of fabrics becomes practical without sacrificing much generality compared to fiber-based techniques

Procedure-Aware Pretraining for Instructional Video Understanding

Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a key challenge in procedure understanding is to be able to extract from unlabeled videos the procedural knowledge such as the identity of the task (e.g., 'make latte'), its steps (e.g., 'pour milk'), or the potential next steps given partial progress in its execution. Our main insight is that instructional videos depict sequences of steps that repeat between instances of the same or different tasks, and that this structure can be well represented by a Procedural Knowledge Graph (PKG), where nodes are discrete steps and edges connect steps that occur sequentially in the instructional activities. This graph can then be used to generate pseudo labels to train a video representation that encodes the procedural knowledge in a more accessible form to generalize to multiple procedure understanding tasks. We build a PKG by combining information from a text-based procedural knowledge database and an unlabeled instructional video corpus and then use it to generate training pseudo labels with four novel pre-training objectives. We call this PKG-based pre-training procedure and the resulting model Paprika, Procedure-Aware PRe-training for Instructional Knowledge Acquisition. We evaluate Paprika on COIN and CrossTask for procedure understanding tasks such as task recognition, step recognition, and step forecasting. Paprika yields a video representation that improves over the state of the art: up to 11.23% gains in accuracy in 12 evaluation settings. Implementation is available at https://github.com/salesforce/paprika.Comment: CVPR 202

Computationally-Mediated Interactions with Traditional Textile Crafts

Crafting is a fundamental part of humanity; it gives us purpose and satisfaction, and it produces items that are beautiful and functional. At the same time, our relationship to traditional physical crafts has seen a massive upheaval due to technological advancements. The freedom and support to create textile crafts for pleasure and passion rather than necessity has never been more widespread. Interdisciplinary explorations of computer science and textile crafts have been increasing due to more people being intrinsically motivated to craft, more forms of supportive technology constantly being built, and more interconnected communities growing via the internet. The work in this dissertation begins to coalesce these user-focused and craft-based experiences by presenting crafting as a series of interconnected and nested processes covering the design, manufacture, and experience of textile craft products. Within these processes, I examine how crafters experience physical and digital forms of agency, both high and low, as well as ludic engagement or the lack thereof, as a means of evaluating user perception of technology related to textiles. As exemplar artifacts, I present my own, as well as collaborative, research on design support software, a manufacturing machine appropriated as a game console, and a pair of electronic textile-based fidget toys. This research illustrates how many varied design choices affected audiences' agency and ludic engagement by examining crafters' perceptions and skill levels, as well as the craft domain interpretations by accompanying software and hardware. The interdisciplinary work presented in this dissertation crosses the boundaries of creativity support software, computational creativity, game studies, human-computer interaction, and crafting communities outside the realm of academia. More importantly, this research begins to explicitly join predominantly feminine craft and masculine technological communities across all ages for the enrichment of all those involved

The doctoral research abstracts. Vol:10 2016 / Institute of Graduate Studies, UiTM

Foreword: Congratulations to Institute of Graduate Studies on the continuous efforts to publish the 10th issue of the Doctoral Research Abstracts which showcases the research carried out in the various disciplines range from science and technology, business and administration to social science and humanities. This issue captures the novelty of research contributed by seventy (70) PhD graduands receiving their scrolls in the UiTM’s 85th Convocation. As of October 2016, this year UiTM has produced 138 PhD graduates soaring from125 in the previous year (2015). It shows that UiTM is in the positive direction to achive the total of 1200 PhD graduates in 2020. To the 70 doctorates, I would like it to be known that you have most certainly done UiTM proud by journeying through the scholarly world with its endless challenges and obstacles, and by persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into more innovative research from knowledge gained during this academic journey, for the community and country. This year marks UiTM’s 60th Anniversary and we have been producing many good quality graduates that have a major impact on the socio-economic development of the country and the bumiputeras. As alumni of UiTM, we hold you dear to our hearts. We sincerely wish you all the best and may the Almighty guide you to a path of excellence and success. As you leave the university as alumni we hope a new relationship will be fostered between you and the faculty in soaring UiTM to greater heights. “UiTM Sentiasa di Hati Ku” / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

Influence of Dynamic Multiaxial Transverse Loading on Ultrahigh Molecular Weight Polyethylene Single Fiber Failure

High performance fibers such as ultrahigh molecular weight polyethylene (UHMWPE) are often used for ballistic impact applications in the form of textile fabrics and composite laminates. In order to predict the ballistic performance of such materials, single-fiber experiments are performed to quantify the material behavior at smaller length scales, which can be applied to larger length scales as a result. Failure of UHMWPE is well understood as a function of simple tension at low and high strain rates, as well as under various multiaxial loading states. However, experimental characterization of single UHMWPE fibers under transverse loading at high strain rates (4000-7000 s-1) has not yet been performed due to the lack of available methodology. In this work, a single fiber transverse impact experimental technique is developed at the Army Research Laboratory (ARL) labs. A small-diameter Hopkinson bar is modified to launch custom-designed loading geometries on individual fibers mounted transversely to the path of motion. Load cells at the grips record forces experienced by the fiber, and a high framerate camera captures the test progression and deformation behavior. Loading geometries are all circular with varying radius including a razor (~2 μm), a sharp indenter (20 μm), and a blunt indenter (200 μm), and two impact velocities are chosen, 10 m/s and 20 m/s, which correlate to strain rates of approximately 4320 and 6846 s-1. This novel apparatus and experimental design is used to study the transverse impact behavior of UHMWPE Dyneema® SK76 single fibers with average diameters of 17 um. Failure strain for all groups is significantly reduced relative to existing tensile and quasi-static (QS) transverse loading data. For all the geometries, failure strains are reduced by 46-51%, compared to QS tensile and 12-19% compared to QS transverse, as strain rates increased from 4320-6846 s-1. Compared to high strain rate (1156 s-1) tensile failure strain, significant reduction in failure strains are measured due to transverse impact loading. Failure strains (i) reduced by 28-34% for blunt impact at strain rates 4369-6952 s-1; (ii) reduced by 32-39% for sharp impact at strain rates 4285-6797 s-1 and (iii) reduced by 58-61% for razor impact at strain rates 4307-6789 s-1. For all the geometries, change in strength ranges from +6% to -2%, compared to QS tensile, as strain rates increased from 4320-6846 s-1. Compared to high strain rate tensile strength, changes in strength can range from a slight increase to a significant reduction due to interactions between the rate-dependent increases in stiffness and strength, and strength degradation due to transverse loading. Strength measurements (i) range from +6% to -2% for blunt impact at strain rates 4369-6952 s-1; (ii) range from +4% to -8% for sharp impact at strain rates 4285-6797 s-1 and (iii) range from -28% to -42% for razor impact at strain rates 4307-6789 s-1. The reduction in tensile properties are attributed to the failure mechanism induced by different geometries. While all geometries induce axial compression due to the impact, the loading radius affects the degree of applied transverse shear, where little to no transverse shear is observed in the blunt indenter, an intermediate amount of shear is applied in the sharp indenter, and a high degree of shear is applied by the razor indenter. This conclusion is supported by failure surface images, where blunt impact results in fibrillation characteristic of tensile failure, razor impact results in fiber shearing characteristic of the cutting action of the razor, and the sharp impact demonstrates a mixed amount of both failure modes. The experiments are modeled in LS-DYNA using a custom user material model (UMAT) to incorporate nonlinear inelastic transverse compressive behavior. Model predictions correlate well to the experimental observations in terms of load and strain values as well as in qualitative characterization of the material response to impact loading. A previously-developed strain-based single fiber multiaxial failure criterion is discussed and applied to the model output, but more development is necessary for this criterion to have predictive capabilities for high strain rate impact of UHMWPE