Article
Engineering, Electrical & Electronic
Utkarsh Tripathi, Saran J. Rittvik, Vinay Chamola, Alireza Jolfaei, Ananthakrishna Chintanpalli
Summary: This paper presents a solution that combines a brain-computer interface system and a humanoid robot for remote teaching. Using Kinect and deep learning algorithms, the system can understand the emotional state of the trainee and enable real-time communication through the humanoid robot.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Dongrui Wu, Bao-Liang Lu, Bin Hu, Zhigang Zeng
Summary: A brain-computer interface (BCI) allows direct communication between a user and a computer through the central nervous system. An affective BCI (aBCI) monitors and regulates the emotional state of the brain, which has various applications in human cognition, communication, decision-making, and health. This tutorial provides a comprehensive and up-to-date guide on aBCIs, covering basic concepts, components of a closed-loop aBCI system, representative applications, and challenges and opportunities in aBCI research and applications.
PROCEEDINGS OF THE IEEE
(2023)
Review
Computer Science, Information Systems
Sze Chit Leong, Yuk Ming Tang, Chung Hin Lai, C. K. M. Lee
Summary: Emotion is a crucial factor influencing human decision-making and communication. Affective computing, focused on developing computational systems that can understand and respond to human emotions, has gained significant attention in the field of human-computer interaction. This systematic review addresses the methodological gaps in previous studies by examining the usage of emotion models and hardware in machine-enabled automated visual emotion recognition. Numerous relevant papers were analyzed, resulting in the identification of popular techniques and current trends. The review provides a comprehensive overview of the topic and offers insights on methodological aspects, facilitating the implementation of visual emotion recognition techniques in various fields.
COMPUTER SCIENCE REVIEW
(2023)
Article
Engineering, Electrical & Electronic
Guoying Zhao, Xiaobai Li, Yante Li, Matti Pietikainen
Summary: Micro-expression (ME) is an involuntary, fleeting, and subtle facial expression that can provide essential clues to people's true feelings. In recent years, ME analysis, especially automatic ME analysis in computer vision, has gained much attention due to its practical importance. This survey provides a comprehensive review of ME development in the field of computer vision, discussing various computational ME analysis methods and future directions.
PROCEEDINGS OF THE IEEE
(2023)
Review
Computer Science, Artificial Intelligence
Renan Vinicius Aranha, Cleber Gimenez Correa, Fatima L. S. Nunes
Summary: The study focuses on the impact of Affective Computing in promoting user engagement in computer applications, with a systematic literature review of available articles discussing emotion recognition techniques and challenges to be overcome in the field.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Omer Sumer, Patricia Goldberg, Sidney DMello, Peter Gerjets, Ulrich Trautwein, Enkelejda Kasneci
Summary: Student engagement is crucial for effective learning and teaching. This study focuses on analyzing student engagement in real classroom settings using computer vision methods. The researchers collected audiovisual recordings of secondary school classes and used deep embeddings for attentional and affective features to train engagement classifiers. The best performing classifiers achieved high AUC scores, with attention-based features being more effective than affective features. Additionally, personalization using just 60 seconds of person-specific data resulted in improved performance.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Bing Yin, Shi Yin, Cong Liu, Yanyong Zhang, Changfeng Xi, Baocai Yin, Zhenhua Ling
Summary: Due to the high cost of manual annotations, the labelled data may be insufficient for training a high-performance dynamic facial expression (DFR) recogniser. To address this issue, the authors propose a multi-modal pre-training method with a pseudo-label guidance mechanism, making use of unlabelled video data to learn informative representations of facial expressions. Experimental results on the Dynamic Facial Expression in the Wild dataset demonstrate the superiority of the proposed method.
IET COMPUTER VISION
(2023)
Article
Computer Science, Information Systems
Satya Prakash Yadav
Summary: Face mining involves discovering patterns within a group of images, utilizing knowledge from various fields. Facial recognition analyzes and identifies features from facial images. This study evaluates the performance of different methods in recognizing seven different facial expressions of two individuals, aiming to discuss the most effective techniques for facial recognition.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Joao Almeida, Luis Vilaca, Ines N. Teixeira, Paula Viana
Summary: Research has made progress in facial expression recognition methods, but insufficient attention has been paid to the visual techniques used to convey emotions in films. Therefore, this study aims to identify emotions in cinema through facial expression analysis, providing a comprehensive overview of relevant datasets and evaluating the feasibility of using facial expressions to determine emotional charge in films.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Nadir Kamel Benamara, Mikel Val-Calvo, Jose Ramon Alvarez-Sanchez, Alejandro Diaz-Morcillo, Jose Manuel Ferrandez-Vicente, Eduardo Fernandez-Jover, Tarik Boudghene Stambouli
Summary: This study proposes a facial emotion recognition system that achieves state-of-the-art performance by utilizing deep convolutional neural networks and label smoothing technique to handle miss-labelled training data. The system can recognize facial emotions in just 13.48 ms (GPU) and 141.97 ms (CPU).
INTEGRATED COMPUTER-AIDED ENGINEERING
(2021)
Article
Computer Science, Hardware & Architecture
Victor M. M. Garcia-Molla, Pedro Alonso-Jorda
Summary: Border tracking in binary images is crucial in computer vision applications. This paper presents a parallel algorithm that can run on multicore computers for border tracking, and compares it with the GPU algorithm. The results indicate that the GPU algorithm performs poorly for large images or images with multiple borders, while the multicore algorithm efficiently handles large images.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Siddharth, Tzyy-Ping Jung, Terrence J. Sejnowski
Summary: This research applies novel deep-learning-based methods to analyze and evaluate four publicly available multi-modal emotion datasets containing bio-sensing and video data. The algorithms outperform previous studies in emotion classification and set benchmarks for new datasets. The research also overcomes inconsistencies between datasets using transfer learning and proposes a new technique for identifying salient brain regions corresponding to affective states.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Review
Computer Science, Artificial Intelligence
Sicheng Zhao, Xingxu Yao, Jufeng Yang, Guoli Jia, Guiguang Ding, Tat-Seng Chua, Bjorn W. Schuller, Kurt Keutzer
Summary: This survey comprehensively reviews the development of affective image content analysis (AICA) in the past two decades, focusing on the state-of-the-art methods and addressing three main challenges. It provides an overview of emotion representation models, available datasets, and compares representative approaches in emotion feature extraction, learning methods, and AICA-based applications. The survey also discusses future research directions and challenges in the field.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Ramprakash Srinivasan, Aleix M. Martinez
Summary: Research reveals differences in the use of facial expressions across cultures and in cultural-specific expressions, with cross-cultural expressions conveying emotion categories and valence while cultural-specific expressions convey valence and arousal. The number of expressions used to communicate each emotion also varies.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2021)
Article
Computer Science, Information Systems
Mohammed Alonazi, Hala J. Alshahrani, Faiz Abdullah Alotaibi, Mohammed Maray, Mohammed Alghamdi, Ahmed Sayed
Summary: Facial emotion recognition is a crucial AI-driven technology that utilizes computer vision techniques to decode and understand emotional expressions displayed on human faces. It can automatically detect and classify a wide range of emotions using deep neural networks, but faces challenges such as variations in lighting, poses, and facial expressions.
Review
Computer Science, Cybernetics
Julia Seitz, Ivo Benke, Armin Heinzl, Alexander Maedche
Summary: Video meeting systems are widely used in work and life, but their impact on users' psychological states and outcomes is not well understood. This article provides a comprehensive review of existing research on psychological user states and outcomes, highlighting key findings and suggesting future research directions.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Alberto Monge Roffarello, Luigi De Russis
Summary: This paper presents a novel digital self-control tool called StepByStep, which proactively assists users in learning how to better manage smartphone use and reduce time spent on their devices. Preliminary studies show promising results in helping users change unwanted smartphone habits.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Evania L. Fasya, Esther van den Bos, Dirk K. J. Heylen, Mariska E. Kret
Summary: This study explores the relationship between mimicry, person-perception, and social anxiety levels by having participants interact with virtual humans. The results show that participants, regardless of anxiety levels, mimic the virtual humans' smiles, which is associated with increased liking and trust towards the virtual humans.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Naseem Ahmadpour, Ajit G. Pillai, Sofia Yao, Andrew Weatherall
Summary: Virtual Reality (VR) can be used in pediatric hospitals to create makerspaces that provide children with an enriched experience. Through observation of participants' engagement with VR, we identified three different maker identities and provided design considerations for makerspaces in pediatric settings.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Michael Jones, Mia Caminita, Elizabeth Klemm, Dustin Bruening, Sarah Ridge
Summary: This study conducted interviews with figure skating coaches to explore their perception of using IMU data in training. The findings indicate that coaches play a crucial role as gatekeepers in sharing and interpreting data, considering individual athletes' needs and being cautious when sharing data with parents.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Abhraneil Dam, Arsh Siddiqui, Charles Leclercq, Myounghoon Jeon
Summary: This article investigates the concept of audio augmented reality (AAR) and provides a systematic understanding, classification, and definition for AAR. The research identifies three categories for AAR applications - Environment Connected, Goal Directed, and Context Adapted, each with three subcategories. This taxonomy serves as a guide for the development and evaluation of AAR applications.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Minjung Kim, Saebyeol Kim, Jinwoo Kim, Tae-Jin Song, Yuyoung Kim
Summary: This study investigates the differences in explanation needs between clinicians and patients in the healthcare domain, and designs corresponding explanation interfaces for each group. The results demonstrate that there are diverse motivations and requirements for seeking explanations among different stakeholders, and the designed interfaces effectively address these needs.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Leonardo Vasconcelos, Jean Zahn, Daniela Trevisan, Jose Viterbo
Summary: In today's world, crowdsourcing initiatives have gained wide adoption. However, sporadic use alone is not enough for success in crowdsourcing initiatives, as active user engagement is crucial. To address this, an 18-card deck was created to provide designers with domain-specific insights on boosting user engagement. Through collaborative online design workshops, valuable information was provided, leading to contributions in design research and practices in crowdsourcing initiatives, particularly in user engagement.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Nikol Figalova, Hans-Joachim Bieg, Julian Elias Reiser, Yuan-Cheng Liu, Martin Baumann, Lewis Chuang, Olga Pollatos
Summary: With increasing automation, drivers' roles transition from active operators to passive system supervisors, affecting their behaviour and cognitive processes. This study investigates attentional resource allocation and subjective cognitive load during different levels of driving automation. The findings suggest that during automated driving, drivers allocate fewer attentional resources to processing environmental information, highlighting the importance of managing drivers' attention and cognitive load for enhancing automation safety and user interface design.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Majid Nasirinejad, Derek Reilly
Summary: Mobile Focus+Context (mF+C) involves using a handheld device as a focus screen for content on an immersive display or mobile projector. In this study, three techniques for linking focus and context were compared, and it was found that all techniques were able to mitigate poor projection quality and performed similarly in terms of time and precision. However, the effectiveness of each technique depended on the task type.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Huiyu Li, Linwei Fan, Chengwei Yang, Yongxia Zhang
Summary: This study evaluates human perception of curvature gain under different virtual path conditions using a novel psychophysical method of limits. The results show that the direction and length of the curved path can impact human perception, and longer pre-order paths can increase the ability to adapt to the post-order path.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Eugene Hwang, Jeongmi Lee
Summary: This study proposes an automatic lecture video editing pipeline based on individual attention patterns, aiming to address the setbacks in producing effective educational videos. The results show that attention-based automatic editing can significantly reduce editing time while maintaining similar video characteristics to professionally edited versions, and have the potential to decrease the cognitive load of learners.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Robin Neuhaus, Ronda Ringfort-Felner, Shadan Sadeghian, Marc Hassenzahl
Summary: Virtual reality has the potential to extend human capabilities beyond reality, but it is unclear whether users perceive augmentation-oriented designs as augmenting and whether the experience is beneficial. Two consecutive experimental vignette studies were conducted to compare reality-oriented designs and augmentation-oriented designs. The findings show that augmentation-oriented designs create a more intensive augmentation experience, which is positively related to positive affect, need fulfillment, usage intention, and hedonic quality. Additionally, a new measure for assessing the subjective experience of augmentation was successfully established.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Moritz Held, Andreea Minculescu, Jochem W. Rieger, Jelmer P. Borst
Summary: In this study, the effects of interventions by adaptive automation systems designed to prevent mind-wandering while driving were predicted. It was found that a simple secondary task can improve driving performance, but if the driving task is simple, people may start mind-wandering, which interferes with driving. The study showed that interventions eliciting mild cognitive load can mitigate the negative effects of mind-wandering on driving performance.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)
Article
Computer Science, Cybernetics
Nannan Xi, Oguz Oz Buruk, Juan Chen, Shiva Jabari, Juho Hamari
Summary: This study investigates the features of wearables that lead to a heightened game experience, finding that integrability to games, wearability, modularity, and sociability are the most important dimensions.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2024)