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30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Tahmid, Ibrahim Asadullah North, Chris Davidson, Kylie Whitley, Kirsten Bowman, Doug Computer Science Virginia Tech BlacksburgVA United States Department of Computer Science Virginia Tech BlacksburgVA United States Center for Human-Computer Interaction Virginia Tech BlacksburgVA United States Department of Defense College ParkMD United States

ISBN: (纸本)9798400713064

Sensemaking is a complex task that places a heavy cognitive demand on individuals. With the recent surge in data availability, making sense of vast amounts of information has become a significant challenge for many professionals, such as intelligence analysts. Immersive technologies such as mixed reality offer a potential solution by providing virtually unlimited space to organize data. However, the difficulty of processing, filtering relevant information, and synthesizing insights remains. We proposed using eye-tracking data from mixed reality head-worn displays to derive the analyst's perceived interest in documents and words, and convey that part of the mental model to the analyst. The global interest of the documents is reflected in their color, and their order on the list, while the local interest of the documents is used to generate focused recommendations for a document. To evaluate these recommendation cues, we conducted a user study with two conditions: a gaze-aware system, EyeST, and a "Freestyle"system without gaze-based visual cues. Our findings reveal that the EyeST helped analysts stay on track by reading more essential information while avoiding distractions. However, this came at the cost of reduced focused attention and perceived system performance. The results of our study highlight the need for explainable AI in human-AI collaborative sensemaking to build user trust and encourage the integration of AI outputs into the immersive sensemaking process. Based on our findings, we offer a set of guidelines for designing gaze-driven recommendation cues in an immersive environment. © 2025 Copyright held by the owner/author(s).

关键词： Information filtering

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Ensemble Knowledge Distillation for Federated Semi-Supervised Image Classification

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Tsinghua science and Technology 2025年第1期30卷 112-123页

作者： Ertong Shang Hui Liu Jingyang Zhang Runqi Zhao Junzhao Du School of Computer Science and Technology Xidian UniversityXi’an 710126China Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of EducationXi’an 710126China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi’an 710126China

Federated learning is an emerging privacy-preserving distributed learning paradigm,in which many clients collaboratively train a shared global model under the orchestration of a remote *** current works on federated learning have focused on fully supervised learning settings,assuming that all the data are annotated with ground-truth ***,this work considers a more realistic and challenging setting,Federated Semi-Supervised Learning(FSSL),where clients have a large amount of unlabeled data and only the server hosts a small number of labeled *** to reasonably utilize the server-side labeled data and the client-side unlabeled data is the core challenge in this *** this paper,we propose a new FSSL algorithm for image classification based on consistency regularization and ensemble knowledge distillation,called *** algorithm uses the global model as the teacher in consistency regularization methods to enhance both the accuracy and stability of client-side unsupervised learning on unlabeled ***,we introduce an additional ensemble knowledge distillation loss to mitigate model overfitting during server-side retraining on labeled *** experiments on several image classification datasets show that our EKDFSSL outperforms current baseline methods.

关键词： federated learning semi-supervised learning federated semi-supervised learning knowledge distillation

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Automated Facial Expression Recognition and Age Estimation Using Deep Learning

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computers, Materials & Continua 2022年第6期71卷 5235-5252页

作者： Syeda Amna Rizwan Yazeed Yasin Ghadi Ahmad Jalal Kibum Kim Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAbu Dhabi122612UAE Department of Human-Computer Interaction Hanyang UniversityAnsan15588Korea

With the advancement of computer vision techniques in surveillance systems,the need for more proficient,intelligent,and sustainable facial expressions and age recognition is *** main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor *** proposed system first takes an input image pre-process it and then detects faces in the entire *** that landmarks localization helps in the formation of synthetic face mask prediction.A novel set of features are extracted and passed to a classifier for the accurate classification of expressions and age *** proposed system is tested over two benchmark datasets,namely,the Gallagher collection person dataset and the Images of Groups *** system achieved remarkable results over these benchmark datasets about recognition accuracy and computational *** proposed system would also be applicable in different consumer application domains such as online business negotiations,consumer behavior analysis,E-learning environments,and emotion robotics.

关键词： Feature extraction face expression model local transform features and recurrent neural network(RNN)

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Process hyper-relation knowledge graph construction and application 7

Process hyper-relation knowledge graph construction and appl...

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2024 7th International Conference on Intelligent Manufacturing and Automation, IMA 2024

作者： Lv, Yang Wang, Peiyan Ji, Guiyang Wang, Libang School of Computer Science Shenyang Aerospace University Shenyang110134 China Liaoning Prof. Technology Innovation Center on Knowledge Engineering and Human-Computer Interaction Shenyang110134 China

A knowledge graph enables the structured representation of process knowledge. Traditional knowledge graphs typically represent process fact knowledge by depicting relations between entities. However, higher-order knowledge, such as causality, coupling, and rationale among process facts, should be addressed. The Process Hyper-relational knowledge graph (PHKG) was proposed to address these shortcomings. It comprises three layers: a concept layer representing process concept knowledge, an instance layer representing process fact knowledge, and a hyper-relationship layer representing higher-order knowledge linking process facts. Employing a semi-automatic construction method, a hyper-relation knowledge graph was created with 1, 602 entities, 2, 509 entity relationships, and 231 pairs of hyper-relationships. A process knowledge reasoning algorithm has also been developed to enable applications to reason about process knowledge. © Published under licence by IOP Publishing Ltd.

关键词： Knowledge graph

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A 2D Geometry Based Grasping Pose Generation Algorithm for a Two-Finger Robot Hand 31

A 2D Geometry Based Grasping Pose Generation Algorithm for a...

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31st International Conference on Electrical Engineering, ICEE 2023

作者： Akbari, Arash Akbari, Arman Masouleh, Mehdi Tale University of Tehran Department of Computer Science Tehran Iran School of Electrical and Computer Engineering Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798350312560

Robot grasping is of paramount importance in industrial and service robotics. In recent years, various data-driven algorithms have been proposed to solve the problem of grasp detection and a part of them are based on reinforcement learning (RL) approaches. In a variety of proposed algorithms, random key points are being employed which will make the learning process inefficient and time-consuming. In this paper, a geometry-based algorithm is presented which can find grasp poses based on the geometry of the unknown object and propose the ones which may lead to successful grasping. For the grasp contacts computation part, the presented algorithm produces a finite number of key points based on the 2D shape of the object from a specific point of view. Afterward, it will narrow down the candidate points and output a finite number of successful grasp poses based on three grasp quality metrics for various unknown objects. Three approaches are proposed in order to achieve center points which can describe different parts of a 2D shape. Then, the obtained points are used as the center of circles which are tangent to the 2D shape contour. Also, a new grasp quality metric is proposed. The time of the grasp and the amount of object disorientation after grasping are considered as a metric to evaluate the successfulness of the grasp. Simulation results demonstrate that the proposed algorithm for unknown object grasping can find a finite number of successful grasp poses for different seen or unseen objects without using any random point © 2023 IEEE.

关键词： Geometry

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Don’t You Worry ’bout a Thing? Identification and Quantification of Relevant Privacy Parameters Within the Acceptance of AAL Technology 7th

Don’t You Worry ’bout a Thing? Identification and Quanti...

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7th and 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2021 and ICT4AWE 2022

作者： Maidhof, Caterina Offermann, Julia Ziefle, Martina Chair of Communication Science Human Computer Interaction Center RWTH Aachen University Campus Boulevard Aachen Germany

ISBN: (纸本)9783031374951

To combat healthcare challenges Ambient Assisted Living (AAL) technologies offer the opportunity to support an independent life in older age. Although the potential and advantages of such technology are acknowledged, perceived barriers in particular referred to privacy still represent a hurdle for their acceptance. Applying a two-step empirical approach, this study aimed at the identification and quantification of relevant privacy parameters for the acceptance of visual AAL technology. First, a qualitative study investigated the participants’ cognitive privacy representations in a scenario in which AAL was installed in their own home to support life in older age. 12 participants (age range: 23–81 years) shared their opinions within semi-structured interviews. Based on these findings, an online survey (N = 134) study was applied in a second step in order to quantify the identified privacy parameters. Overall, the paper presents the qualitative key findings as well as the descriptive results of the quantitative study. The results show the usefulness of both methods to a) identify and understand thought processes of potential users regarding privacy requirements as well as b) to get insights into the relevance and meaning of the identified privacy parameters. The qualitative and quantitative findings are useful to inform technical designers as well as lawmakers to consider the privacy parameters during technology or law development. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Parameter estimation

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Virtual Displays for Knowledge Work: Extending or Replacing Physical Monitors for More Flexibility and Screen Space

Virtual Displays for Knowledge Work: Extending or Replacing ...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Leonardo Pavanatto Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech USA

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

In this paper, we explore the potential of virtual displays in sup-porting knowledge work, focusing on scenarios where conventional physical monitors fall short. Our research investigates the feasibility and productivity costs of extending or replacing physical monitors with augmented and virtual reality displays. We present three com-pelling use cases, illustrating how virtual displays enhance flexibility, adaptability, and customization in remote and diverse work settings. Lessons learned from user studies highlight hardware and interface design challenges, emphasizing the need for larger resolution and field of view in head-worn displays (HWD). We conclude the paper with research opportunities and a call to address the evolving demands of knowledge work interfaces.

关键词： Productivity Three-dimensional displays Head-mounted displays Focusing Virtual reality User interfaces Hardware

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Planet Purifiers: A Collaborative Immersive Experience Proposing New Modifications to HOMER and Fishing Reel interaction Techniques

Planet Purifiers: A Collaborative Immersive Experience Propo...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Alexander Giovannelli Fionn Murphy Trey Davis Chaerin Lee Rehema Abulikemu Matthew Gallagher Sahil Sharma Lee Lisle Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech Blacksburg VA USA

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

This paper presents our solution to the 2025 3DUI Contest challenge. We aimed to develop a collaborative, immersive experience that raises awareness about trash pollution in natural landscapes while enhancing traditional interaction techniques in virtual environments. To achieve these objectives, we created an engaging multiplayer game where one user collects harmful pollutants while the other user provides medication to impacted wildlife using enhancements to traditional interaction techniques: HOMER and Fishing Reel. We enhanced HOMER to use a cone volume to reduce the precise aiming required by a selection raycast to provide a more efficient means to collect pollutants at large distances, coined as FLOW-MATCH. To improve the animal feed distribution to wildlife far away from the user with Fishing Reel, we created RAWR-XD, an asymmetric bi-manual technique to more conveniently adjust the reeling speed using the non-selecting wrist rotation of the user.

关键词： Wrist Three-dimensional displays Pollution Planets Wildlife Collaboration Virtual environments Immersive experience Games Food products

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CrowdSolve: Managing Tensions in an Expert-Led Crowdsourced Investigation

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Proceedings of the ACM on human-computer interaction 2021年第CSCW1期5卷 1-30页

作者： Venkatagiri, Sukrit Gautam, Aakash Luther, Kurt Department Of Computer Science Center For Human-Computer Interaction Virginia Tech-1 ArlingtonVA United States

Investigators in fields such as journalism and law enforcement have long sought the public's help with investigations. New technologies have also allowed amateur sleuths to lead their own crowdsourced investigations-that have traditionally only been the purview of expert investigators-with mixed results. Through an ethnographic study of a four-day, co-located event with over 250 attendees, we examine the human infrastructure responsible for enabling the success of an expert-led crowdsourced investigation. We find that the experts enabled attendees to generate useful leads;the attendees formed a community around the event;and the victims' families felt supported. Additionally, the co-located setting, legal structures, and emergent social norms impacted collaborative work practice. We also surface three important tensions to consider in future investigations and provide design recommendations to manage these tensions. © 2021 ACM.

关键词： Crowdsourcing

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SEED-VII: A Multimodal Dataset of Six Basic Emotions with Continuous Labels for Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第02期16卷 969-985页

作者： Jiang, Wei-Bang Liu, Xuan-Hao Zheng, Wei-Long Lu, Bao-Liang Shanghai Jiao Tong University Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Shanghai200240 China

Recognizing emotions from physiological signals is a topic that has garnered widespread interest, and research continues to develop novel techniques for perceiving emotions. However, the emergence of deep learning has highlighted the need for comprehensive and high-quality emotional datasets that enable the accurate decoding of human emotions. To systematically explore human emotions, we develop a multimodal dataset consisting of six basic (happiness, sadness, fear, disgust, surprise, and anger) emotions and the neutral emotion, named SEED-VII. This multimodal dataset includes electroencephalography (EEG) and eye movement signals. The seven emotions in SEED-VII are elicited by 80 different videos and fully investigated with continuous labels that indicate the intensity levels of the corresponding emotions. Additionally, we propose a novel Multimodal Adaptive Emotion Transformer (MAET), that can flexibly process both unimodal and multimodal inputs. Adversarial training is utilized in the MAET to mitigate subject discrepancies, which enhances domain generalization. Our extensive experiments, encompassing both subject-dependent and cross-subject conditions, demonstrate the superior performance of the MAET in terms of handling various inputs. Continuous labels are used to filter the data with high emotional intensity, and this strategy is proven to be effective for attaining improved emotion recognition performance. Furthermore, complementary properties between the EEG signals and eye movements and stable neural patterns of the seven emotions are observed. © 2010-2012 IEEE.

关键词： Eye movements

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