Parameter tweaking is a common task in various design scenarios. For example, in color enhancement of photographs, designers tweak multiple parameters such as "brightness" and "contrast" to obtain ...the best visual impression. Adjusting one parameter is easy; however, if there are multiple correlated parameters, the task becomes much more complex, requiring many trials and a large cognitive load. To address this problem, we present a novel extension of
Bayesian optimization
techniques, where the system decomposes the entire parameter tweaking task into a sequence of one-dimensional
line search
queries that are easy for human to perform by manipulating a single slider. In addition, we present a novel concept called
crowd-powered visual design optimizer
, which queries crowd workers, and provide a working implementation of this concept. Our
single-slider manipulation
microtask design for crowdsourcing accelerates the convergence of the optimization relative to existing comparison-based microtask designs. We applied our framework to two different design domains: photo color enhancement and material BRDF design, and thereby showed its applicability to various design domains.
Geometric modeling and the physical validity of shapes are traditionally considered independently. This makes creating aesthetically pleasing yet physically valid models challenging. We propose an ...interactive design framework for efficient and intuitive exploration of geometrically and physically valid shapes. During any geometric editing operation, the proposed system continuously visualizes the valid range of the parameter being edited. When one or more constraints are violated after an operation, the system generates multiple suggestions involving both discrete and continuous changes to restore validity. Each suggestion also comes with an editing mode that simultaneously adjusts multiple parameters in a coordinated way to maintain validity. Thus, while the user focuses on the aesthetic aspects of the design, our
computational design
framework helps to achieve physical realizability by providing active guidance to the user. We demonstrate our framework on plank-based furniture design with nail-joint and frictional constraints. We use our system to design a range of examples, conduct a user study, and also fabricate a physical prototype to test the validity and usefulness of the system.
This paper presents a method that employs parametric surfaces as surface geometry representations at any stage of a computational process to compute self-supporting surfaces. This approach can be ...differentiated from existing relevant methods because such methods represent surfaces by a triangulated mesh surface or a network consisting of lines. The proposed method is based on the theory of Airy stress functions. Although some existing methods are also based on this theory, they apply its discrete version to discrete geometries. The proposed method simultaneously applies the theory to parametric surfaces directly and the discrete theory to the edges of parametric patches. The discontinuous boundary between continuous patches naturally corresponds to ribs seen in traditional vault masonry buildings. We use nonuniform rational B-spline surfaces in this study; however, the basic idea can be applied to other parametric surfaces. A variety of self-supporting surfaces obtained by the proposed computational scheme is presented.
Generative models based on deep neural networks often have a high-dimensional latent space, ranging sometimes to a few hundred dimensions or even higher, which typically makes them hard for a user to ...explore directly. We propose differential subspace search to allow efficient iterative user exploration in such a space, without relying on domain- or data-specific assumptions. We develop a general framework to extract low-dimensional subspaces based on a local differential analysis of the generative model, such that a small change in such a subspace would provide enough change in the resulting data. We do so by applying singular value decomposition to the Jacobian of the generative model and forming a subspace with the desired dimensionality spanned by a given number of singular vectors stochastically selected on the basis of their singular values, to maintain ergodicity. We use our framework to present 1D subspaces to the user via a 1D slider interface. Starting from an initial location, the user finds a new candidate in the presented 1D subspace, which is in turn updated at the new candidate location. This process is repeated until no further improvement can be made. Numerical simulations show that our method can better optimize synthetic black-box objective functions than the alternatives that we tested. Furthermore, we conducted a user study using complex generative models and the results show that our method enables more efficient exploration of high-dimensional latent spaces than the alternatives.
As-rigid-as-possible shape manipulation Igarashi, Takeo; Moscovich, Tomer; Hughes, John F
ACM transactions on graphics,
07/2005, Letnik:
24, Številka:
3
Journal Article
Recenzirano
Odprti dostop
We present an interactive system that lets a user move and deform a two-dimensional shape without manually establishing a skeleton or freeform deformation (FFD) domain beforehand. The shape is ...represented by a triangle mesh and the user moves several vertices of the mesh as constrained handles. The system then computes the positions of the remaining free vertices by minimizing the distortion of each triangle. While physically based simulation or iterative refinement can also be used for this purpose, they tend to be slow. We present a two-step closed-form algorithm that achieves real-time interaction. The first step finds an appropriate rotation for each triangle and the second step adjusts its scale. The key idea is to use quadratic error metrics so that each minimization problem becomes a system of linear equations. After solving the simultaneous equations at the beginning of interaction, we can quickly find the positions of free vertices during interactive manipulation. Our approach successfully conveys a sense of rigidity of the shape, which is difficult in space-warp approaches. With a multiple-point input device, even beginners can easily move, rotate, and deform shapes at will.
Repetitive patterns are ubiquitous in natural and human-made objects, and can be created with a variety of tools and methods. Manual authoring provides unmatched degree of freedom and control, but ...can require significant artistic expertise and manual labor. Computational methods can automate parts of the manual creation process, but are mainly tailored for discrete pixels or elements instead of more general continuous structures. We propose an example-based method to synthesize continuous curve patterns from exemplars. Our main idea is to extend prior sample-based discrete element synthesis methods to consider not only sample positions (geometry) but also their connections (topology). Since continuous structures can exhibit higher complexity than discrete elements, we also propose robust, hierarchical synthesis to enhance output quality. Our algorithm can generate a variety of continuous curve patterns fully automatically. For further quality improvement and customization, we also present an autocomplete user interface to facilitate interactive creation and iterative editing. We evaluate our methods and interface via different patterns, ablation studies, and comparisons with alternative methods.
We present a novel interactive tool for garment design that enables, for the first time, interactive bidirectional editing between 2D patterns and 3D high-fidelity simulated draped forms. This ...provides a continuous, interactive, and natural design modality in which 2D and 3D representations are simultaneously visible and seamlessly maintain correspondence. Artists can now interactively edit 2D pattern designs and immediately obtain stable accurate feedback online, thus enabling rapid prototyping and an intuitive understanding of complex drape form.
In this article, we introduce an efficient and versatile numerical aerodynamics model for general three-dimensional geometry shapes in potential flow. The proposed model has low computational cost ...and achieves an accuracy of moderate fidelity for the aerodynamic loads for a given glider shape. In the geometry preprocessing steps of our model, lifting-wing surfaces are recognized, and wake panels are generated automatically along the trailing edges. The proposed aerodynamics model improves the potential theory-based panel method. Furthermore, a new quadratic expression for aerodynamic forces and moments is proposed. It consists of geometry-dependent aerodynamic coefficient matrices and has a continuous representation for the drag/lift-force coefficients. Our model enables natural and real-time aerodynamics simulations combined with general rigid-body simulators for interactive animation. We also present a design system for original gliders. It uses an assembly-based modeling interface and achieves interactive feedback by leveraging the partwise precomputation enabled by our method. We illustrate that one can easily design various flyable gliders using our system.
Medicine is an important application area for deep learning models. Research in this field is a combination of medical expertise and data science knowledge. In this paper, instead of 2D medical ...images, we introduce an open-access 3D intracranial aneurysm dataset, IntrA, that makes the application of points-based and mesh-based classification and segmentation models available. Our dataset can be used to diagnose intracranial aneurysms and to extract the neck for a clipping operation in medicine and other areas of deep learning, such as normal estimation and surface reconstruction. We provide a large-scale benchmark of classification and part segmentation by testing state-of-the-art networks. We also discuss the performance of each method and demonstrate the challenges of our dataset. The published dataset can be accessed here: https://github.com/intra2d2019/IntrA.
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