An official website of the United States government
The ability to visually discern shape, form, and value is fundamental to observational drawing. However, developing this skill requires a drawer to perceive a “raw” version of the scene being drawn, often referred to as regaining the innocence of the eye. This work investigates how interactive projected light cues can be used to alter the perception of drawing objects and understand how users might control their own perception. We introduce an augmented reality system capable of dynamically projecting interactive light cues onto objects within a live drawing studio. We present the design of three cues that address challenging percepts for novice drawers: gauging proportion, discerning shape, and shifting visual attention. In a formal user study with novice and intermediate drawers, we evaluate the effectiveness of these cues in supporting observational drawing. We demonstrate how cues can be designed to correct subconscious errors and visually guide users in learning to draw.
more »
« less
Shape Structuralizer: Design, Fabrication, and User-driven Iterative Refinement of 3D Mesh Models
Current Computer-Aided Design (CAD) tools lack proper support for guiding novice users towards designs ready for fabrication. We propose Shape Structuralizer (SS), an interactive design support system that repurposes surface models into structural constructions using rods and custom 3Dprinted joints. Shape Structuralizer embeds a recommendation system that computationally supports the user during design ideation by providing design suggestions on local refinements of the design. This strategy enables novice users to choose designs that both satisfy stress constraints as well as their personal design intent. The interactive guidance enables users to repurpose existing surface mesh models, analyze them in-situ for stress and displacement constraints, add movable joints to increase functionality, and attach a customized appearance. This also empowers novices to fabricate even complex constructs while ensuring structural soundness. We validate the Shape Structuralizer tool with a qualitative user study where we observed that even novice users were able to generate a large number of structurally safe designs for fabrication.
more »
« less
- Award ID(s):
- 1632154
- PAR ID:
- 10112930
- Date Published:
- Journal Name:
- Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems Paper No. 663
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Modern CAD tools represent 3D designs not only as geometry, but also as a program composed of geometric operations, each of which depends on a set of parameters. Program representations enable meaningful and controlled shape variations via parameter changes. However, achieving desired modifications solely through parameter editing is challenging when CAD models have not been explicitly authored to expose select degrees of freedom in advance. We introduce a novel bidirectional editing system for 3D CAD programs. In addition to editing the CAD program, users can directly manipulate 3D geometry and our system infers parameter updates to keep both representations in sync. We formulate inverse edits as a set of constrained optimization objectives, returning plausible updates to program parameters that both match user intent and maintain program validity. Our approach implements an automatically differentiable domain‐specific language for CAD programs, providing derivatives for this optimization to be performed quickly on any expressed program. Our system enables rapid, interactive exploration of a constrained 3D design space by allowing users to manipulate the program and geometry interchangeably during design iteration. While our approach is not designed to optimize across changes in geometric topology, we show it is expressive and performant enough for users to produce a diverse set of design variants, even when the CAD program contains a relatively large number of parameters.more » « less
-
In architectural design, architects explore a vast amount of design options to maximize various performance criteria, while adhering to specific constraints. In an effort to assist architects in such a complex endeavour, we propose IDOME, an interactive system for computer-aided design optimization. Our approach balances automation and control by efficiently exploring, analyzing, and filtering space layouts to inform architects' decision-making better. At each design iteration, IDOME provides a set of alternative building layouts which satisfy user-defined constraints and optimality criteria concerning a user-defined space parametrization. When the user selects a design generated by IDOME, the system performs a similar optimization process with the same (or different) parameters and objectives. A user may iterate this exploration process as many times as needed. In this work, we focus on optimizing built environments using architectural metrics by improving the degree of visibility, accessibility, and information gaining for navigating a proposed space. This approach, however, can be extended to support other kinds of analysis as well. We demonstrate the capabilities of IDOME through a series of examples, performance analysis, user studies, and a usability test. The results indicate that IDOME successfully optimizes the proposed designs concerning the chosen metrics and offers a satisfactory experience for users with minimal training.more » « less
-
Recent robot collections provide various interactive tools for users to explore and analyze their datasets. Yet, the literature lacks data on how users interact with these collections and which tools can best support their goals. This late-breaking report presents preliminary data on the utility of four interactive tools for accessing a collection of robot hands. The tools include a gallery and similarity comparison for browsing and filtering existing hands, a prediction tool for estimating user impression of hands (e.g., humanlikeness), and a recommendation tool suggesting design features (e.g., number of fingers) for achieving a target user impression rating. Data from a user study with 9 novice robotics researchers suggest the users found the tools useful for various tasks and especially appreciated the gallery and recommendation functionalities for understanding the complex relationships of the data. We discuss the results and outline future steps for developing interface design guidelines for robot collections.more » « less
-
Procedural modeling has produced amazing results, yet fundamental issues such as controllability and limited user guidance persist. We introduce a novel procedural system called PICO (Procedural Iterative Constrained Optimizer) using PICO-Graph, a procedural model designed with optimization in mind. PICO enables the exploration of generative designs by combining user and environmental constraints into a single framework and using optimization without the need to write procedural rules. The PICO-Graph is a data-flow procedural model consisting of a set of geometry-generating operation nodes. The forward generation is initiated by sending geometric objects from initial nodes. These objects travel through the graph, triggering generation of more objects along the way. We combine the PICO-Graph with evolutionary optimization that allows for exploration of the generated models and the generation of variants. The user defines the geometry-generating operations and the set of constraints; e.g, whether an existing object should be supported by the generated model, whether symmetries exist, etc. PICO then generates geometric models that fulfill the constraints through optimization, allowing interactive user control of constraints. We show PICO on a variety of examples, including generation of procedural chairs, generation of support structures for 3D printing, or generation of procedural terrains matching a given input.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3290605.3300893
