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检索条件"任意字段=Proceedings of the ACM SIGGRAPH Symposium on User Interface Software and Technology"

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TRAvel Slicer: Continuous Extrusion Toolpaths for 3D Printing 24

TRAvel Slicer: Continuous Extrusion Toolpaths for 3D Printin...

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37th acm Annual symposium on user interface software and technology (UIST)

作者： Gould, Jaime Friedman-Gerlicz, Camila Buechley, Leah Univ New Mexico Albuquerque NM 87131 USA

ISBN: (纸本)9798400706288

In this paper we present Travel Reduction Algorithm (TRAvel) Slicer, which minimizes travel movements in 3D printing. Conventional slicing software generates toolpaths with many travel movements-movements without material extrusion. Some 3D printers are incapable of starting and stopping extrusion and it is difficult to impossible to control the extrusion of many materials. This makes toolpaths with travel movements unsuitable for a wide range of printers and materials. We developed the open-source TRAvel Slicer to enable the printing of complex 3D models on a wider range of printers and in a wider range of materials than is currently possible. TRAvel Slicer minimizes two different kinds of travel movements-what we term Inner- and Outer-Model travel. We minimize Inner-Model travel (travel within the 3D model) by generating space-filling Fermat spirals for each contiguous planar region of the model. We minimize Outer-Model travel (travels outside of the 3D model) by ordering the printing of different branches of the model, thus limiting transitions between branches. We present our algorithm and software and then demonstrate how: 1) TRAvel Slicer makes it possible to generate high-quality prints from a metal-clay material, CeraMetal, that is functionally unprintable using an off-the-shelf slicer. 2) TRAvel Slicer dramatically increases the printing efficiency of traditional plastic 3D printing compared to an off-the-shelf slicer.

关键词： Slicing software g-code generation Traveling Salesman Problem Direct Write 3D Printing Clay 3D Printing Fused Filament Fabrication

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HandPad: Make Your Hand an On-the-go Writing Pad via Human Capacitance 24

HandPad: Make Your Hand an On-the-go Writing Pad via Human C...

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Lu, Yu Ding, Dian Pan, Hao Li, Yijie Zhou, Juntao Fu, Yongjian Zhang, Yongzhao Chen, Yi-Chao Xue, Guangtao Shanghai Jiao Tong University Shanghai China Central South University Changsha China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798400706288

The convenient text input system is a pain point for devices such as AR glasses, and it is difficult for existing solutions to balance portability and efficiency. This paper introduces HandPad, the system that turns the hand into an on-the-go touchscreen, which realizes interaction on the hand via human capacitance. HandPad achieves keystroke and handwriting inputs for letters, numbers, and Chinese characters, reducing the dependency on capacitive or pressure sensor arrays. Specifically, the system verifies the feasibility of touch point localization on the hand using the human capacitance model and proposes a handwriting recognition system based on Bi-LSTM and ResNet. The transfer learning-based system only needs a small amount of training data to build a handwriting recognition model for the target user. Experiments in real environments verify the feasibility of HandPad for keystroke (accuracy of 100%) and handwriting recognition for letters (accuracy of 99.1%), numbers (accuracy of 97.6%) and Chinese characters (accuracy of 97.9%). © 2024 acm.

关键词： Character recognition

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AniCraft: Crafting Everyday Objects as Physical Proxies for Prototyping 3D Character Animation in Mixed Reality 24

AniCraft: Crafting Everyday Objects as Physical Proxies for ...

引用

37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Li, Boyu Yuan, Linping Yan, Zhe Liu, Qianxi Shen, Yulin Wang, Zeyu Guangzhou China Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9798400706288

We introduce AniCraft, a mixed reality system for prototyping 3D character animation using physical proxies crafted from everyday objects. Unlike existing methods that require specialized equipment to support the use of physical proxies, AniCraft only requires affordable markers, webcams, and daily accessible objects and materials. AniCraft allows creators to prototype character animations through three key stages: selection of virtual characters, fabrication of physical proxies, and manipulation of these proxies to animate the characters. This authoring workflow is underpinned by diverse physical proxies, manipulation types, and mapping strategies, which ease the process of posing virtual characters and mapping user interactions with physical proxies to animated movements of virtual characters. We provide a range of cases and potential applications to demonstrate how diverse physical proxies can inspire user creativity. user experiments show that our system can outperform traditional animation methods for rapid prototyping. Furthermore, we provide insights into the benefits and usage patterns of different materials, which lead to design implications for future research. © 2024 acm.

关键词： Animation

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StyleFactory: Towards Better Style Alignment in Image Creation through Style-Strength-Based Control and Evaluation 24

StyleFactory: Towards Better Style Alignment in Image Creati...

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Zhou, Mingxu Zhang, Dengming You, Weitao Yu, Ziqi Wu, Yifei Pan, Chenghao Liu, Huiting Lao, Tianyu Chen, Pei College of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China

ISBN: (纸本)9798400706288

Generative AI models have been widely used for image creation. However, generating images that are well-aligned with users' personal styles on aesthetic features (e.g., color and texture) can be challenging due to the poor style expression and interpretation between humans and models. Through a formative study, we observed that participants showed a clear subjective perception of the desired style and variations in its strength, which directly inspired us to develop style-strength-based control and evaluation. Building on this, we present StyleFactory, an interactive system that helps users achieve style alignment. Our interface enables users to rank images based on their strengths in the desired style and visualizes the strength distribution of other images in that style from the model's perspective. In this way, users can evaluate the understanding gap between themselves and the model, and define well-aligned personal styles for image creation through targeted iterations. Our technical evaluation and user study demonstrate that StyleFactory accurately generates images in specific styles, effectively facilitates style alignment in image creation workflow, stimulates creativity, and enhances the user experience in human-AI interactions. © 2024 acm.

关键词： Human-Model Style Alignment

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Mul-O: Encouraging Olfactory Innovation in Various Scenarios Through a Task-Oriented Development Platform 24

Mul-O: Encouraging Olfactory Innovation in Various Scenarios...

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37th acm Annual symposium on user interface software and technology (UIST)

作者： Gao, Peizhong Liu, Fan Wen, Di Gao, Yuze Zhang, Linxin Wang, Chikelei Zhang, Qiwei Zhang, Yu Ma, Shao-en Lu, Qi Mi, Haipeng Xu, Yingqing Tsinghua Univ Beijing Peoples R China Tsinghua Univ Future Lab Beijing Peoples R China Carnegie Mellon Univ Pittsburgh PA 15213 USA Natl Key Lab Human Factors Engn Beijing Peoples R China

ISBN: (纸本)9798400706288

Olfactory interfaces are pivotal in HCI, yet their development is hindered by limited application scenarios, stifling the discovery of new research opportunities. This challenge primarily stems from existing design tools focusing predominantly on odor display devices and the creation of standalone olfactory experiences, rather than enabling rapid adaptation to various contexts and tasks. Addressing this, we introduce Mul-O, a novel task-oriented development platform crafted to aid semi-professionals in navigating the diverse requirements of potential application scenarios and effectively prototyping ideas. Mul-O facilitates the swift association and integration of olfactory experiences into functional designs, system integrations, and concept validations. Comprising a web UI for task-oriented development, an API server for seamless third-party integration, and wireless olfactory display hardware, Mul-O significantly enhances the ideation and prototyping process in multisensory tasks. This was verified by a 15-day workshop attended by 30 participants. The workshop produced seven innovative projects, underscoring Mul-O's efficacy in fostering olfactory innovation.

关键词： Smell Smell-augmented interactive system Olfactory interface Smell experience Development kit design Task-oriented

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VizGroup: An AI-assisted Event-driven System for Collaborative Programming Learning Analytics 24

VizGroup: An AI-assisted Event-driven System for Collaborati...

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Tang, Xiaohang Wong, Sam Pu, Kevin Chen, Xi Yang, Yalong Chen, Yan Department of Computer Science Virginia Tech BlacksburgVA United States University of Washington SeattleWA United States Department of Computer Science University of Toronto TorontoON Canada School of Interactive Computing Georgia Institute of Technology AtlantaGA United States

ISBN: (纸本)9798400706288

Programming instructors often conduct collaborative learning activities, like Peer Instruction, to foster a deeper understanding in students and enhance their engagement with learning. These activities, however, may not always yield productive outcomes due to the diversity of student mental models and their ineffective collaboration. In this work, we introduce VizGroup, an AI-assisted system that enables programming instructors to easily oversee students' real-time collaborative learning behaviors during large programming courses. VizGroup leverages Large Language Models (LLMs) to recommend event specifications for instructors so that they can simultaneously track and receive alerts about key correlation patterns between various collaboration metrics and ongoing coding tasks. We evaluated VizGroup with 12 instructors in a comparison study using a dataset collected from a Peer Instruction activity that was conducted in a large programming lecture. The results showed that VizGroup helped instructors effectively overview, narrow down, and track nuances throughout students' behaviors. © 2024 acm.

关键词： Collaborative learning

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Wheeler: A Three-Wheeled Input Device for Usable, Efficient, and Versatile Non-Visual Interaction 24

Wheeler: A Three-Wheeled Input Device for Usable, Efficient,...

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Islam, Md Touhidul Sojib, Noushad Kabir, Imran Amit, Ashiqur Rahman Amin, Mohammad Ruhul Billah, Syed Masum College of Information Sciences and Technology Pennsylvania State University University ParkPA United States Cognitive Assistive Robotics Lab University of New Hampshire DurhamNH United States Innovation Garage Limited Dhaka Bangladesh Computer and Information Science Fordham University BronxNY United States

ISBN: (纸本)9798400706288

Blind users rely on keyboards and assistive technologies like screen readers to interact with user interface (UI) elements. In modern applications with complex UI hierarchies, navigating to different UI elements poses a significant accessibility challenge. users must listen to screen reader audio descriptions and press relevant keyboard keys one at a time. This paper introduces Wheeler, a novel three-wheeled, mouse-shaped stationary input device, to address this issue. Informed by participatory sessions, Wheeler enables blind users to navigate up to three hierarchical levels in an app independently using three wheels instead of navigating just one level at a time using a keyboard. The three wheels also offer versatility, allowing users to repurpose them for other tasks, such as 2D cursor manipulation. A study with 12 blind users indicates a significant reduction (40%) in navigation time compared to using a keyboard. Further, a diary study with our blind co-author highlights Wheeler's additional benefits, such as accessing UI elements with partial metadata and facilitating mixed-ability collaboration. © 2024 acm.

关键词： Wheels

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Empower Real-World BCIs with NIRS-X: An Adaptive Learning Framework that Harnesses Unlabeled Brain Signals 24

Empower Real-World BCIs with NIRS-X: An Adaptive Learning Fr...

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37th acm Annual symposium on user interface software and technology (UIST)

作者： Wang, Liang Zhang, Jiayan Liu, Jinyang McKeon, Devon Brizan, David Guy Blaney, Giles Jacob, Robert J. K. Tufts Univ Medford MA 02155 USA Univ San Francisco San Francisco CA USA Northeastern Univ Boston MA 02115 USA Google Llc Cambridge MA USA

ISBN: (纸本)9798400706288

Brain-Computer interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS) hold promise for future interactive user interfaces due to their ease of deployment and declining cost. However, they typically require a separate calibration process for each user and task, which can be burdensome. Machine learning helps, but faces a data scarcity problem. Due to inherent inter-user variations in physiological data, it has been typical to create a new annotated training dataset for every new task and user. To reduce dependence on such extensive data collection and labeling, we present an adaptive learning framework, NIRS-X, to harness more easily accessible unlabeled fNIRS data. NIRS-X includes two key components: NIR-Siam and NIRSformer. We use the NIRSiam algorithm to extract generalized brain activity representations from unlabeled fNIRS data obtained from previous users and tasks, and then transfer that knowledge to new users and tasks. In conjunction, we design a neural network, NIRSformer, tailored for capturing both local and global, spatial and temporal relationships in multi-channel fNIRS brain input signals. By using unlabeled data from both a previously released fNIRS2MW visual n-back dataset and a newly collected fNIRS2MW audio n-back dataset, NIRS-X demonstrates its strong adaptation capability to new users and tasks. Results show comparable or superior performance to supervised methods, making NIRS-X promising for real-world fNIRS-based BCIs.

关键词： BCI Brain-Computer interface neural networks data augmentation fNIRS n-back task machine learning cognitive workload near-infrared spectroscopy implicit interfaces end-to-end self-supervised learning contrastive learning transfer learning

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Selfrionette: A Fingertip Force-Input Controller for Continuous Full-Body Avatar Manipulation and Diverse Haptic Interactions 24

Selfrionette: A Fingertip Force-Input Controller for Continu...

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Hashimoto, Takeru Hirao, Yutaro The University of Tokyo Bunkyo Tokyo Japan Nara Institute of Science and Technology Ikoma Nara Japan

ISBN: (纸本)9798400706288

We propose Selfrionette, a controller that uses fingertip force input to drive avatar movements in virtual reality (VR). This system enables users to interact with virtual objects and walk in VR using only fingertip force, overcoming physical and spatial constraints. Additionally, by fixing users' fingers, it provides users with counterforces equivalent to the applied force, allowing for diverse and wide dynamic range haptic feedback by adjusting the relationship between force input and virtual movement. To evaluate the effectiveness of the proposed method, this paper focuses on hand interaction as a first step. In user Study 1, we measured usability and embodiment during reaching tasks under Selfrionette, body tracking, and finger tracking conditions. In user Study 2, we investigated whether users could perceive haptic properties such as weight, friction, and compliance under the same conditions as user Study 1. Selfrionette was found to be comparable to body tracking in realism of haptic interaction, enabling embodied avatar experiences even in limited spatial conditions. © 2024 Owner/Author.

关键词： Virtual reality

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Tyche: Making Sense of PBT Effectiveness 24

Tyche: Making Sense of PBT Effectiveness

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37th Annual acm symposium on user interface software and technology, UIST 2024

作者： Goldstein, Harrison Tao, Jeffrey Hatfield-Dodds, Zac Pierce, Benjamin C. Head, Andrew Computer and Information Science University of Pennsylvania PhiladelphiaPA United States Anthropic San FranciscoCA United States

ISBN: (纸本)9798400706288

software developers increasingly rely on automated methods to assess the correctness of their code. One such method is property-based testing (PBT), wherein a test harness generates hundreds or thousands of inputs and checks the outputs of the program on those inputs using parametric properties. Though powerful, PBT induces a sizable gulf of evaluation: developers need to put in nontrivial effort to understand how well the different test inputs exercise the software under test. To bridge this gulf, we propose Tyche, a user interface that supports sensemaking around the effectiveness of property-based tests. Guided by a formative design exploration, our design of Tyche supports developers with interactive, configurable views of test behavior with tight integrations into modern developer testing workflow. These views help developers explore global testing behavior and individual test inputs alike. To accelerate the development of powerful, interactive PBT tools, we define a standard for PBT test reporting and integrate it with a widely used PBT library. A self-guided online usability study revealed that Tyche's visualizations help developers to more accurately assess software testing effectiveness. © 2024 Owner/Author.

关键词： user interfaces

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