Image based surface reflectance remapping for consistent and tool independent material appearence

Physically-based rendering in Computer Graphics requires the knowledge of material properties other than 3D shapes, textures and colors, in order to solve the rendering equation. A number of material models have been developed, since no model is currently able to reproduce the full range of available materials. Although only few material models have been widely adopted in current rendering systems, the lack of standardisation causes several issues in the 3D modelling workflow, leading to a heavy tool dependency of material appearance. In industry, final decisions about products are often based on a virtual prototype, a crucial step for the production pipeline, usually developed by a collaborations among several departments, which exchange data. Unfortunately, exchanged data often tends to differ from the original, when imported into a different application. As a result, delivering consistent visual results requires time, labour and computational cost. This thesis begins with an examination of the current state of the art in material appearance representation and capture, in order to identify a suitable strategy to tackle material appearance consistency. Automatic solutions to this problem are suggested in this work, accounting for the constraints of real-world scenarios, where the only available information is a reference rendering and the renderer used to obtain it, with no access to the implementation of the shaders. In particular, two image-based frameworks are proposed, working under these constraints. The first one, validated by means of perceptual studies, is aimed to the remapping of BRDF parameters and useful when the parameters used for the reference rendering are available. The second one provides consistent material appearance across different renderers, even when the parameters used for the reference are unknown. It allows the selection of an arbitrary reference rendering tool, and manipulates the output of other renderers in order to be consistent with the reference

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Real-time simulation and visualisation of cloth using edge-based adaptive meshes

Real-time rendering and the animation of realistic virtual environments and characters has progressed at a great pace, following advances in computer graphics hardware in the last decade. The role of cloth simulation is becoming ever more important in the quest to improve the realism of virtual environments. The real-time simulation of cloth and clothing is important for many applications such as virtual reality, crowd simulation, games and software for online clothes shopping. A large number of polygons are necessary to depict the highly exible nature of cloth with wrinkling and frequent changes in its curvature. In combination with the physical calculations which model the deformations, the effort required to simulate cloth in detail is very computationally expensive resulting in much diffculty for its realistic simulation at interactive frame rates. Real-time cloth simulations can lack quality and realism compared to their offline counterparts, since coarse meshes must often be employed for performance reasons. The focus of this thesis is to develop techniques to allow the real-time simulation of realistic cloth and clothing. Adaptive meshes have previously been developed to act as a bridge between low and high polygon meshes, aiming to adaptively exploit variations in the shape of the cloth. The mesh complexity is dynamically increased or refined to balance quality against computational cost during a simulation. A limitation of many approaches is they do not often consider the decimation or coarsening of previously refined areas, or otherwise are not fast enough for real-time applications. A novel edge-based adaptive mesh is developed for the fast incremental refinement and coarsening of a triangular mesh. A mass-spring network is integrated into the mesh permitting the real-time adaptive simulation of cloth, and techniques are developed for the simulation of clothing on an animated character

Social Reconstruction of New Ventures' Liabilities of Newness and Smallness: An Example From the French Technology Sector

New entrepreneurial ventures are intrinsically stigmatized by liabilities of newness and smallness that lead to lack of legitimacy. The legitimacy problem complicates new ventures’ access to external resources. Overcoming these liabilities means gaining legitimacy in the eyes of significant audiences (Stinchcombe, 1965; Singh, Tucker & House, 1986). To date, the research on new ventures’ legitimation has mainly taken one of the following two perspectives: the neo-institutional perspective, in which scholars view new ventures legitimation as a product of conformity with institutional norms and standards, and the strategic perspective, in which scholars focus on new ventures’ proactive symbolic actions aimed at manipulating audiences’ perceptions. Although existing studies of liabilities of newness and smallness rest on the assumption that new ventures’ lack of legitimacy is inter-subjective, the social-constructionist aspect of this phenomenon has not been sufficiently investigated. For instance, extant studies have overlooked entrepreneurs’ subjective experiences ensuing from their ventures’ lack of legitimacy. Emerging literature on the sensemaking of entrepreneurial failures partly fills this knowledge gap. These studies have examined how entrepreneurs cognitively process and narratively construct their ventures’ failures (e. g. Cardon et al, 2011; Mantere et al, 2013). However, these studies focus on ultimate failures, rather than failed attempts to acquire external resources. Continued inability to acquire key resources, being a direct premise of entrepreneurial failures, has not been studied as a subject of sensemaking. Therefore, this study seeks to understand how entrepreneurs make sense of and narratively construct experienced hardship of resource acquisition at the early years of their ventures’ existence. Furthermore, although scholars acknowledge that public perception influences the way entrepreneurs’ make sense of their ventures’ failures (e. g. Cardon et al, 2011), extant literature failed to explain what constitutes public perception of entrepreneurial failures. Therefore, this study also seeks to understand how entrepreneurs’ narrative construction of failures and hardship affects public perception. To fulfil the research objectives, this study is based on a synthesis of the literatures on new ventures legitimation, entrepreneurial failures and social movements (e. g. Benford & Snow, 2000). Social movement approach provides suitable theoretical and methodological framework for the research endeavour. Social movement studies explore how collective discontent is made sense of, grievances are articulated and framed as injustice by social actors in pursuit of social change (Turner, 1995). In this study, narratives of entrepreneurs whose ventures’ development is hampered by inability to access external resources are examined. The empirical investigation is focused on the new ventures’ attempts to establish collaborative technology partnerships with incumbents. Frame analysis (Goffman, 1974; Creed et al, 2002a) is adapted to critically examine entrepreneurs’ narratives collected through very in-depth interviews. The data set comprised narrative interviews with 35 entrepreneurs and 16 top managers of private and public organizations in France. The findings of this study suggest that failed attempts to establish technology partnerships with incumbents trigger entrepreneurs’ sensemaking of their own experiences and also broader reinterpretation of technology partnership as a patterned social interaction. It was found that the entrepreneurs whose ventures’ development is hampered by inability to access incumbents’ resources are likely to frame their hardship as injustice rather than simple misfortune or mistake. The findings also indicate that injustice frame plays twofold role in the entrepreneurial dynamics. Besides being an interpretive and blame externalizing mental model, injustice frame also plays a sensegiving role. It is demonstrated that when framing their hardship as injustice, entrepreneurs employ contextually embedded discourse to construct collective identities of new ventures and incumbents that ascribe role expectations to resource-holding incumbents. Furthermore, relevance to experience and cultural resonance of the injustice frame determines its appropriation by other actors and, therefore, its impact on the public discourse

Sustainable Fashion and Textile Recycling

The clothing and textile industry is a resource-intensive industry and accounts for 3 to 10 percent of global carbon dioxide emissions. In addition, the industry is extremely linear and generates large amounts of waste. For the industry to move from a linear to a circular economy, several solutions are required along the value chain: upstream by working with resource efficiency, the longevity of textile products, and preventing waste; and downstream with techniques for sorting and recycling. In addition, solutions for traceability and transparency need to be developed and coordinated as accepted methods for sustainability measurements. This Special Issue (SI) "Sustainable Fashion and Textile Recycling" brings together areas of knowledge along the textile value chain to highlight the difficulties and opportunities that exist from both a broader perspective and in specific issues. In this SI, these 11 papers are mainly devoted to new research in traceability, design, textile production, and recycling. Each valuable article included in this Special Issue contributes fundamental knowledge for a transformation of the textile and fashion industry to take place. Numerous studies, solutions, and ideas need to be carried out to create the innovations that will become the reality of our future. Likewise, we need to learn from each other and take advantage of all the fantastic knowledge that is generated globally every day towards a better future for generations to come

Global Trade in the Emerging Business Environment

Global Trade in the Emerging Business Environment explores global trade dynamics in the emerging business environment. Globalization, technological advancements, Industry 4.0, China’s Belt and Road Initiative, and the COVID-19 pandemic are changing the global trade ecosystem. Companies and countries need to evaluate these rapid changes and adjust their respective business strategies and policy formulations. This book discusses such strategies and how firms and countries can reposition themselves within the current environment

Legitimate distinctiveness via cultural entrepreneurship in new ventures

"To be different or to be the same?" Taking an ambidextrous perspective, I argue that new ventures can acquire legitimacy through their identity claims that communicate both distinctiveness and conformity. Adopting a cultural entrepreneurship process model, I submit that both competitive distinctiveness and institutional conformity can individually serve as legitimating strategies in identity development by forming propriety judgements and that legitimacy mediates the relationship between distinctiveness, conformity and performance. Moreover, I suggest that these relationships will be contingent upon validity judgments of category appeal.I develop theory around, and test, the relationship between competitive distinctiveness and pragmatic legitimacy and challenge the longstanding path-dependent assertion that prioritizes conformity. I argue that (1) competitive distinctiveness, by itself, can lead to legitimacy; (2) identity claims with high distinctiveness and low conformity can generate positive outcomes: and (3) the strength of competitive distinctiveness-performance and institutional conformity-performance relationships are contingent upon the level of category appeal. To test the hypotheses, I conduct two separate studies: (1) an experimental design, and (2) quantitative study of a social media (i.e., Twitter) dataset.There are five main contributions of this dissertation. First, this study adds precision to the construct of legitimate distinctiveness by finding support for both distinctiveness and conformity can be associated with positive outcomes. It also enhances precision in the cultural entrepreneurship process by modeling and testing pragmatic legitimacy and normative legitimacy as mediators. Second, I answer the call from researchers to examine the effects of institutional and competitive isomorphism simultaneously by testing the effects of competitive distinctiveness and institutional conformity. Third, this study advances research by theorizing and testing the moderating effect of distinctiveness on conformity-performance relationship. Fourth, the findings advance the categorization literature by providing evidence for the moderating role of category appeal on distinctiveness-performance as well as conformity-performance relationship. Fifth, by conducting two separate studies involving two robust designs utilizing datasets sampling two major stakeholder groups, and measuring individual perceptions (i.e., propriety judgements) as well as collective (i.e., validity judgements), I answer the call by researchers to integrate micro and macro perspectives of legitimacy