A bug was found in the codes which resulted in information leak. New experimental results will be updated at a later date. I assume all responsibility for this mistake. KT Ma
For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current methods, i.e. self-reporting, web-activity monitoring and social media mining are either intrusive or require data over long periods of time. Recently, there is growing evidence in cognitive science that a variety of users' profile is significantly correlated with eye-tracking data. We propose a novel just-in-time implicit profiling method, Eye-2-I, which learns the user's interests, demographic and personality traits from the eye-tracking data while the user is watching videos. Although seemingly conspicuous by closely monitoring the user's eye behaviors, our method is unobtrusive and privacy-preserving owing to its unique characteristics, including (1) fast speed - the profile is available by the first video shot, typically few seconds, and (2) self-contained - not relying on historical data or functional modules. [Bug found. As a proof-of-concept, our method is evaluated in a user study with 51 subjects. It achieved a mean accuracy of 0.89 on 37 attributes of user profile with 9 minutes of eye-tracking data.]
SurgGaze: Implicit Calibration for Accurate Gaze Analysis in Operating Rooms with Wearable Eyetrackers
Computer Science and Engineering, University of Michigan（密歇根大学计算机科学与工程系）；Michigan Institute for Data & AI in Society, University of Michigan（密歇根大学数据与人工智能社会研究所）；School of Information, University of Michigan（密歇根大学信息学院）；Medical School, University of Michigan（密歇根大学医学院）
MindEye-OmniAssist: A Gaze-Driven LLM-Enhanced Assistive Robot System for Implicit Intention Recognition and Task Execution
Hubei Key Laboratory of Brain-Inspired Intelligent Systems, Huazhong University of Science and Technology（脑启发智能系统湖北省重点实验室，华中科技大学）；Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（图像处理与智能控制教育部重点实验室，人工智能与自动化学院，华中科技大学）；state key laboratory of intelligent vehicle safety technology, chongqing changan automobile co ltd（智能车辆安全技术 state key laboratory，重庆长安汽车有限公司）；Science and technology innovation center, China ship development and design centre（科技创新中心，中国船舶工业设计研究中心）
