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Constrained maximum weighted bipartite matching:a novel approach to radio broadcast scheduling

science China(Information sciences) 2019年第7期62卷 156-169页

作者： Shaojiang WANG Tianyong WU Yuan YAO Dongbo BU Shaowei CAI State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences

Given a set of radio broadcast programs, the radio broadcast scheduling problem is to allocate a set of devices to transmit the programs to achieve the optimal sound quality. In this article, we propose a complete algorithm to solve the problem, which is based on a branch-and-bound(BnB) algorithm. We formulate the problem with a new model, called constrained maximum weighted bipartite matching(CMBM),i.e., the maximum matching problem on a weighted bipartite graph with constraints. For the reduced matching problem, we propose a novel BnB algorithm by introducing three new strategies, including the highest quality first, the least conflict first and the more edge first. We also establish an upper bound estimating function for pruning the search space of the algorithm. The experimental results show that our new algorithm can quickly find the optimal solution for the radio broadcast scheduling problem at small scales, and has higher scalability for the problems at large scales than the existing complete algorithm.

关键词： radio broadcast scheduling branch-and-bound algorithm constrained maximum weighted bipartite matching Kuhn-Munkres algorithm strategy combinations

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Gesture interaction in virtual reality

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Virtual Reality & Intelligent Hardware 2019年第1期1卷 84-112页

作者： Yang LI Jin HUANG Feng TIAN Hong-An WANG Guo-Zhong DAI Beijing Key Laboratory of Human-Computer Interaction Institute of SoftwareChinese Academy of SciencesBeijing 100190China State Key Laboratory of Computer Science Chinese Academy of SciencesBeijing 100190China

With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of *** is one of the most important communication methods of human beings,which can effectively express users'*** the past few decades,gesture-based interaction has made significant *** article focuses on the gesture interaction technology and discusses the definition and classification of gestures,input devices for gesture interaction,and gesture interaction recognition *** application of gesture interaction technology in virtual reality is studied,the existing problems in the current gesture interaction are summarized,and the future development is prospected.

关键词： Virtual reality Gesture interaction Gesture recognition

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Non-Frontal Facial Expression Recognition Using a Depth-Patch Based Deep Neural Network

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Journal of computer science & Technology 2017年第6期32卷 1172-1185页

作者： Nai-Ming Yao Hui Chen Qing-Pei Guo Hong-An Wang Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Bcijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China

The challenge of coping with non-frontal head poses during facial expression recognition results in considerable reduction of accuracy and robustness when capturing expressions that occur during natural communications. In this paper, we attempt to recognize facial expressions under poses with large rotation angles from 2D videos. A depth^patch based 4D expression representation model is proposed. It was reconstructed from 2D dynamic images for delineating continuous spatial changes and temporal context under non-frontal cases. Furthermore, we present an effective deep neural network classifier, which can accurately capture pose-variant expression features from the depth patches and recognize non-frontal expressions. Experimental results on the BU-4DFE database show that the proposed method achieves a high recognition accuracy of 86.87% for non-frontal facial expressions within a range of head rotation angle of up to 52%, outperforming existing methods. We also present a quantitative analysis of the components contributing to the performance gain through tests on the BU-4DFE and Multi-PIE datasets.

关键词： facial expression recognition non-frontal head pose depth spatial-temporal convolutional neural network

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Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony

arXiv

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arXiv 2025年

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions—first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © 2025, CC BY-NC-SA.

关键词： Neurons

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Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony 4th

Potential Indicator for Continuous Emotion Arousal by Dyna...

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4th International Workshop on human Brain and Artificial Intelligence, HBAI 2024

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9789819640003

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions-first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electroencephalography (EEG) Emotion Annotation Inter-subject Correlation

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Trajectory prediction model for crossing-based target selection

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Virtual Reality & Intelligent Hardware 2019年第3期1卷 330-340页

作者： Hao ZHANG Jin HUANG Feng TIAN Guozhong DAI Hongan WANG Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of SciencesBeijing 100190China State Key Lab of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Background Crossing-based target selection motion may attain less error rates and higher interactive speed in some *** of the research in target selection fields are focused on the analysis of the interaction ***,as trajectories play a much more important role in crossing-based target selection compared to the other interactive techniques,an ideal model for trajectories can help computer designers make predictions about interaction results during the process of target selection rather than at the end of the whole *** In this paper,a trajectory prediction model for crossing based target selection tasks is proposed by taking the reference of a dynamic model *** Simulation results demonstrate that our model performed well with regard to the prediction of trajectories,endpoints and hitting time for target-selection motion,and the average error of trajectories,endpoints and hitting time values were found to be 17.28%,2.73mm and 11.50%,respectively.

关键词： Target selection Crossing-based selection Trajectory prediction

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Relectrode: A reconfigurable electrode for multi-purpose sensing based on microfluidics 21

Relectrode: A reconfigurable electrode for multi-purpose sen...

引用

2021 CHI Conference on human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021

作者： Sun, Wei Chen, Yanjun Zhan, Simon Han, Teng State Key Laboratory of Computer Science Beijing Key Lab of Human-Computer Interaction Institute of SoftwareChinese Academy of Sciences Beijing China

ISBN: (纸本)9781450380966

In this paper, we propose a reconfgurable electrode, RElectrode, using a microfuidic technique that can change the geometry and material properties of the electrode to satisfy the needs for sensing a variety of diferent types of user input through touch/touchless gestures, pressure, temperature, and distinguish between diferent types of objects or liquids. Unlike the existing approaches, which depend on the specifc-shaped electrode for particular sensing (e.g., coil for inductive sensing), RElectrode enables capacity, inductance, resistance/pressure, temperature, pH sensings all in a single package. We demonstrate the design and fabrication of the microfuidic structure of our RElectrode, evaluate its sensing performance through several studies, and provide some unique applications. RElectrode demonstrates technical feasibility and application values of integrating physical and biochemical properties of microfuidics into novel sensing interfaces. © 2021 ACM.

关键词： Electrodes

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EmotionMap:Visual Analysis of Video Emotional Content on a Map

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Journal of computer science & Technology 2020年第3期35卷 576-591页

作者： Cui-Xia Ma Jian-Cheng Song Qian Zhu Kevin Maher Ze-Yuan Huang Hong-An Wang State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100190China Academy of Arts and Design Tsinghua UniversityBeijing 100084China

Emotion plays a crucial role in gratifying users’needs during their experience of movies and TV series,and may be underutilized as a framework for exploring video content and *** this paper,we present EmotionMap,a novel way of presenting emotion for daily users in 2D geography,fusing spatio-temporal information with emotional *** interface is composed of novel visualization elements interconnected to facilitate video content exploration,understanding,and *** allows understanding of the overall emotion at a glance while also giving a rapid understanding of the ***,we develop EmotionDisc which is an effective tool for collecting audiences’emotion based on emotion representation *** collect audience and character emotional data,and then integrate the metaphor of a map to visualize video content and emotion in a hierarchical *** combines sketch interaction,providing a natural approach for users’active *** novelty and the effectiveness of EmotionMap have been demonstrated by the user study and experts’feedback.

关键词： video visualization emotion analysis visual analysis sketch interaction

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human Decision-making is Susceptible to AI-driven Manipulation

arXiv

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arXiv 2025年

作者： Sabour, Sahand Liu, June M. Liu, Siyang Yao, Chris Z. Cui, Shiyao Zhang, Xuanming Zhang, Wen Cao, Yaru Bhat, Advait Guan, Jian Wu, Wei Mihalcea, Rada Althoff, Tim Lee, Tatia M.C. Huang, Minlie The CoAI Group DCST Institute for Artificial Intelligence Tsinghua University Beijing China State Key Laboratory of Brain and Cognitive Sciences The University of Hong Kong Hong Kong Laboratory of Neuropsychology and Human Neuroscience The University of Hong Kong Hong Kong The LIT Group Department of Computer Science and Engineering University of Michigan Ann Arbor United States Department of Psychology University of International Relations Beijing China Department of Chinese Language and Literature Northwest Minzu University Lanzhou China Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA United States ANT Group China

Artificial Intelligence (AI) systems are increasingly intertwined with daily life, assisting users in executing various tasks and providing guidance on decision-making. This integration introduces risks of AI-driven manipulation, where such systems may exploit users’ cognitive biases and emotional vulnerabilities to steer them toward harmful outcomes. Through a randomized controlled trial with 233 participants, we examined human susceptibility to such manipulation in financial (e.g., purchases) and emotional (e.g., conflict resolution) decision-making contexts. Participants interacted with one of three AI agents: a neutral agent (NA) optimizing for user benefit without explicit influence, a manipulative agent (MA) designed to covertly influence beliefs and behaviors, or a strategy-enhanced manipulative agent (SEMA) employing established psychological tactics to reach its hidden objectives. To ensure participant well-being, this study involved hypothetical scenarios, pre-screening for at-risk individuals, and comprehensive post-study debriefing. By analyzing participants’ decision patterns and shifts in their preference ratings post-interaction, we found significant susceptibility to AI-driven manipulation. Particularly, across both decision-making domains, participants interacting with the manipulative agents shifted toward harmful options at substantially higher rates (financial, MA: 62.3%, SEMA: 59.6%;emotional, MA: 42.3%, SEMA: 41.5%) compared to the NA group (financial, 35.8%;emotional, 12.8%). Notably, our results reveal that even simple manipulative objectives (MA) can be as effective as employing established psychological strategies (SEMA) in swaying human decision-making. These findings suggest that AI-driven manipulation could become widely spread, as it does not require sophisticated tactics and expertise to influence users. By revealing the potential for covert AI influence, this study highlights a critical vulnerability in human-AI interactions, emphasiz

关键词： Finance

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A unified user behavior model for trajectory-based tasks with different types of path constraints

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science China(Information sciences) 2023年第10期66卷 316-318页

作者： Hao ZHANG Jin HUANG Huawei TU Feng TIAN Guozhong DAI Hongan WANG Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Department of Computer Science and Information Technology La Trobe University

An important research branch of human-computer interaction(HCI) is to develop predictive models for human performance in fundamental interactions [1]. On today's graphical user interface(GUI), users often implicitly perform various trajectory-based interactions, such as navigating through menus [2], entering the boundary of a button,

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