Implicit Decals: Interactive Editing of Repetitive Patterns on Surfaces

11 pagesInternational audienceTexture mapping is an essential component for creating 3D models and is widely used in both the game and the movie industries. Creating texture maps has always been a complex task and existing methods carefully balance flexibility with ease of use. One difficulty in using texturing is the repeated placement of individual textures over larger areas. In this paper we propose a method which uses decals to place images onto a model. Our method allows the decals to compete for space and to deform as they are being pushed by other decals. A spherical field function is used to determine the position and the size of each decal and the deformation applied to fit the decals. The decals may span multiple objects with heterogeneous representations. Our method does not require an explicit parameterization of the model. As such, varieties of patterns including repeated patterns like rocks, tiles, and scales can be mapped. We have implemented the method using the GPU where placement, size, and orientation of thousands of decals are manipulated in real time

Genetics of psycho-emotional well-being: genome-wide association study and polygenic risk score analysis

BackgroundPsycho-emotional well-being is essential for living a life of satisfaction and fulfillment. However, depression and anxiety have become the leading mental health issues worldwide, according to the World Health Organization. Both disorders have been linked to stress and other psychological factors. Their genetic basis remains understudied.MethodsIn 2020–2021, the psycho-emotional well-being of 30,063 Russians with no known psychiatric history was assessed using the Hospital Anxiety and Depression Scale (HADS) for general mental health and the HADS subscale A (anxiety) for anxiety. Following the original instructions, an anxiety score of ≥11 points was used as the anxiety threshold. A genome-wide association study was performed to find associations between anxiety and HADS/HADS-A scores using linear and logistic regressions based on HADS/HADS-A scores as binary and continuous variables, respectively. In addition, the links between anxiety, sociodemographic factors (such as age, sex, and employment), lifestyle (such as physical activity, sleep duration, and smoking), and markers of caffeine and alcohol metabolism were analyzed. To assess the risk of anxiety, polygenic risk score modeling was carried out using open-access software and principal component analysis (PCA) to simplify the calculations (ROC AUC = 89.4 ± 2.2% on the test set).ResultsThere was a strong positive association between HADS/HADS-A scores and sociodemographic factors and lifestyle. New single-nucleotide polymorphisms (SNPs) with genome-wide significance were discovered, which had not been associated with anxiety or other stress-related conditions but were located in genes previously associated with bipolar disorder, schizophrenia, or emotional instability. The CACNA1C variant rs1205787230 was associated with clinical anxiety (a HADS-A score of ≥11 points). There was an association between anxiety levels (HADS-A scores) and genes involved in the activity of excitatory neurotransmitters: PTPRN2 (rs3857647), DLGAP4 (rs8114927), and STK24 (rs9517326).ConclusionOur results suggest that calcium channels and monoamine neurotransmitters, as well as SNPs in genes directly or indirectly affecting neurogenesis and synaptic functions, may be involved in the development of increased anxiety. The role of some non-genetic factors and the clinical significance of physiological markers such as lifestyle were also demonstrated

Model repair and editing tools

With the declining production cost and improvement of scanning technology, three-dimensional model acquisition systems are rapidly becoming more affordable. At the same time, personal computers with graphics hardware capable of displaying complex 3D models have become inexpensive enough to be available to a large population. As a result, there is, potentially, an opportunity to consider new virtual reality uses from areas as diverse as cultural heritage exploration and retail sales applications that will allow people to view associated large classes of realistic 3D objects on home computers and media devices. Although there are many physical techniques for acquiring 3D data, including laser scanners, CT or MRI scans, the basic pipeline of operations (Figure 1.1) lacks a sufficient set of tools to take the acquired data and produce a usable 3D model. This dissertation proposes a set of efficient and robust 3D data reconstruction and editing tools for such a pipeline. We look at the fundamental problems of range scan data completion, modeling, and parameterization. We propose a new cross-parameterization method for efficient calculation of a low-distortion bijective mapping between models. Recent research in digital geometry processing suggests multiple new applications for such a mapping, including pair-wise model editing [11] transferring texture and surface properties (BRDFs, normal maps, etc) [61], and fitting template meshes to multiple data sets [7, 55]. We also extend our cross-parameterization technique to support models with gaps and holes. This allows us to develop a new and robust method for template-based range scan data completion. One of the most significant obstacles in computer graphics is providing easy-to-use tools for creating and editing detailed 3D models. To this end, we present a new set of tools with which non-expert user can create detailed geometric models quickly and easily. In particular, we propose a new modeling system for creating new, original models by mixing and matching parts of pre-existing models. In this way, we eliminate the need for a user to perform complex geometric operations, and thereby reduce the modeling process to that of part selection. This dissertation also proposes a new technique for image-based modeling that allows a user to easily transform a sketch or picture into a 3D model using a 3D template model. The 3D template provides the geometric detail that cannot be inferred from an image alone. This allows the user to create detailed geometric models from pictures alone. We also introduce a real-time editing algorithm that allows the creation of new models through the deformation of existing ones. Our proposed editing algorithm has applications in such common geometric operations as mesh deformation, morphing, and blending. Thus, we propose contributions to the model repair and editing pipeline that simplifies the task of creating and repairing detailed 3D models.Science, Faculty ofComputer Science, Department ofGraduat