惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

云风的 BLOG
云风的 BLOG
V
Visual Studio Blog
人人都是产品经理
人人都是产品经理
The GitHub Blog
The GitHub Blog
月光博客
月光博客
T
Tailwind CSS Blog
小众软件
小众软件
Y
Y Combinator Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
P
Proofpoint News Feed
B
Blog RSS Feed
博客园 - 司徒正美
A
About on SuperTechFans
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - 聂微东
Microsoft Security Blog
Microsoft Security Blog
Recent Announcements
Recent Announcements
博客园 - Franky
U
Unit 42
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Microsoft Azure Blog
Microsoft Azure Blog
T
The Blog of Author Tim Ferriss
GbyAI
GbyAI
Apple Machine Learning Research
Apple Machine Learning Research

cs.HC updates on arXiv.org

From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis
Tiger:Wearable Glasses for the 20-20-20 Rule to Alleviate...
Chulhong Min, Euihyeok Lee, Souneil Park, Seungwoo Kang · 2019-06-12 · via cs.HC updates on arXiv.org

We propose Tiger, an eyewear system for helping users follow the 20-20-20 rule to alleviate the Computer Vision Syndrome symptoms. It monitors user's screen viewing activities and provides real-time feedback to help users follow the rule. For accurate screen viewing detection, we devise a light-weight multi-sensory fusion approach with three sensing modalities, color, IMU, and lidar. We also design the real-time feedback to effectively lead users to follow the rule. Our evaluation shows that Tiger accurately detects screen viewing events, and is robust to the differences in screen types, contents, and ambient light. Our user study shows positive perception of Tiger regarding its usefulness, acceptance, and real-time feedback.