Article
Multidisciplinary Sciences
Zihan Yan, Yue Wu, Yifei Shan, Wenqian Chen, Xiangdong Li
Summary: In this research, the ARGaze dataset was constructed to enable the design of a calibration-free eye tracking device. The dataset includes eye gaze images and augmented reality scene videos, and achieved low gaze estimation error, indicating its significance for generalizing the use of eye tracking.
Article
Chemistry, Analytical
Xingyang Feng, Qingbin Wang, Hua Cong, Yu Zhang, Mianhao Qiu
Summary: This paper presents a method for rapid and stable gaze point tracking by designing a robot system equipped with eyes and a head and implementing a body-head-eye coordinated motion control strategy. Experimental results demonstrate the feasibility of this method based on the three-dimensional coordinates of the target.
Article
Computer Science, Cybernetics
Xin Liu, Yao Zhang, Xianta Jiang, Bin Zheng
Summary: This study examines the effects of task difficulty on human operators' eye movements before hand movements. Results show that participants tend to move their eyes earlier to target and make more eye adjustments when facing a more difficult task.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Psychology, Multidisciplinary
Chloe Callahan-Flintoft, Christian Barentine, Jonathan Touryan, Anthony J. Ries
Summary: By combining head mounted displays (HMDs) with virtual reality (VR), researchers are able to capture more naturalistic vision in an experimentally controlled setting, accurately tracking eye movements as they occur in concert with head movements. This approach allows for easier comparison between HMD studies and previous research that used monitor displays, providing insights into the strengths and weaknesses of recording and classifying eye and head tracking data in VR.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Robotics
Benjamin A. Newman, Reuben M. Aronson, Siddhartha S. Srinivasa, Kris Kitani, Henny Admoni
Summary: The HARMONIC dataset presents a large multimodal dataset capturing human interactions with a robotic arm in a shared autonomy setting designed for assistive eating tasks. It includes data views of various aspects such as eye gaze, body pose, and hand pose, providing valuable resources for researchers interested in intention prediction, human mental state modeling, and shared autonomy studies. The dataset offers data streams in formats like video and human-readable CSV and YAML files.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2022)
Article
Psychology, Mathematical
Bernhard Petersch, Kai Dierkes
Summary: The study focuses on potential errors in pupillometry measurement, specifically looking at eyeball rotation in relation to the recording camera and optical effects due to refraction at corneal interfaces. Through experimental data and synthetic images, a successful correction method is identified, along with discussions on the impact of errors at different levels.
BEHAVIOR RESEARCH METHODS
(2022)
Article
Engineering, Multidisciplinary
Jiahui Hu, Yonghua Lu, Jinhai Zhang, Jiajun Xu, Haozheng Yang
Summary: This paper proposes a monocular free-head gaze-tracking method based on machine learning, constructs two high-precision and real-time gaze-tracking models, and combines the technology with an electric sickbed to create a gaze-controlled sickbed system.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Ting Lei, Jing Chen, Jixiang Chen, Bo Liu
Summary: Eye tracking, as a novel input modality, is widely used in head-mounted displays for interaction due to its natural and fast characteristics. However, eye-based selection often performs poorly in accuracy and stability compared with other input modalities, especially for small targets. To address this issue, we built a likelihood model by modeling the gaze point distribution and combined it with Bayesian rules for probabilistic inference of the intended target as an alternative to traditional selection criteria. Our investigation shows significant improvement in selection performance, especially for small targets, compared to conventional methods and existing optimal likelihood models.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Rula Sami Aleesa, Hossein Mahvash Mohammadi, Amirhassan Monadjemi, Ivan A. Hashim
Summary: In this paper, an efficient method of features extraction using validated statistical approaches is proposed, along with a robust classifier for grammatical facial expressions (GFEs) in facial expression recognition systems. A new dataset is collected from 70 participants, and the features extracted include facial expression, head movement, and eye-gaze. The proposed system achieves a higher accuracy rate of 95% when tested on the American Sign Language (ASL) dataset, compared to previous works.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Psychology, Multidisciplinary
Inka Schmitz, Wolfgang Einhaeuser
Summary: This study investigates how people estimate gaze direction in screen-based communication and found that estimates are more accurate in the horizontal direction, biased towards the sender's head position, and influenced by the repetition of the same sender.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Computer Science, Information Systems
Zakariyya Abdullahi Bature, Sunusi Bala Abdullahi, Suparat Yeamkuan, Werapon Chiracharit, Kosin Chamnongthai
Summary: Due to the vulnerability of eye saccades, people find it challenging to control smart systems with complex gaze gestures. This paper proposes a new set of eye gaze points and head orientation angles as new sequences to recognize complex gaze gestures, which outperformed conventional methods.
Article
Computer Science, Interdisciplinary Applications
Bert Hartfiel, Rainer Stark
Summary: The development of new car interior concepts requires tools that enable subjective experiences and evaluations, with virtual reality technologies being generally suitable for such evaluations but exceptions may exist in state-of-the-art driving simulators. In a validation study comparing primary driving tasks in two HMD-based simulators with test runs in a real car, participants showed more valid behavior in the dynamic system than in the static simulator condition.
Article
Chemistry, Analytical
Yun-Ju Lee, Po-Chieh Lin, Ling-Ying Chen, Yu-Jung Chen, Jing Nong Liang
Summary: This study investigated different swing strategies between professional and amateur batters using IMU and eye-tracking devices. The results showed that professional batters had more rhythmic and efficient body movements, with differences in gaze position and timing of angular velocity compared to the amateur group.
Article
Biology
Sebastian H. Zahler, David E. Taylor, Joey Y. Wong, Julia M. Adams, Evan H. Feinberg
Summary: The study shows that mice can make sensory-guided gaze shifts involving both eye movements and attempted head movements. The flexibility of mouse gaze shifts is revealed under head-fixed conditions, offering insights into the characteristics of mouse gaze shifts and laying the foundation for studying the coupling between head and eye movements.
Article
Chemistry, Analytical
Svetlana Kovalenko, Anton Mamonov, Vladislav Kuznetsov, Alexandr Bulygin, Irina Shoshina, Ivan Brak, Alexey Kashevnik
Summary: Detection of fatigue is crucial for developing preventive systems, and a dataset with both fatigued and normal individuals is required. Our study collected data from 10 participants performing various activities, using an eye tracker, video cameras, stage cameras, and heart rate monitors. We analyzed existing datasets but found none of them fully suitable for fatigue detection.
Article
Oncology
Leonard M. da Silva, Emilio M. Pereira, Paulo G. O. Salles, Ran Godrich, Rodrigo Ceballos, Jeremy D. Kunz, Adam Casson, Julian Viret, Sarat Chandarlapaty, Carlos Gil Ferreira, Bruno Ferrari, Brandon Rothrock, Patricia Raciti, Victor Reuter, Belma Dogdas, George DeMuth, Jillian Sue, Christopher Kanan, Leo Grady, Thomas J. Fuchs, Jorge S. Reis-Filho
Summary: AI-based system Paige Prostate shows high sensitivity and NPV in the diagnosis of prostate cancer, leading to potential improvement in patient care. It can accurately classify histopathology slides into benign or suspicious categories, reducing diagnostic time and improving efficiency.
JOURNAL OF PATHOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov, Hava T. Siegelmann, Terrence J. Sejnowski, Christopher Kanan
Summary: Replay is the reactivation of neural patterns similar to past experiences, believed to play a critical role in memory formation, retrieval, and consolidation. While replay mechanisms have been successfully incorporated in artificial neural networks, there are differences between biological replay and artificial neural network replay. Utilizing aspects of biological replay could potentially enhance artificial neural networks.
NEURAL COMPUTATION
(2021)
Article
Medicine, General & Internal
Usman Mahmood, David D. B. Bates, Yusuf E. Erdi, Lorenzo Mannelli, Giuseppe Corrias, Christopher Kanan
Summary: This study demonstrates the value of using deep learning to map single energy CT scans to synthetic dual-energy CT material density iodine scans for liver segmentation. The results show that training with synthetic DECT scans can achieve good segmentation accuracy with less data on both the held-out and generalization test sets.
Proceedings Paper
Computer Science, Artificial Intelligence
Robik Shrestha, Kushal Kafle, Christopher Kanan
Summary: This paper proposes a new approach to address the problem of dataset bias in deep neural networks by modifying the network architecture and introducing inductive biases. The experiments demonstrate that OccamNets outperform or rival state-of-the-art methods on architectures that incorporate these inductive biases.
COMPUTER VISION, ECCV 2022, PT XX
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Cecilia O. Alm, Reynold Bailey, Hannah Miller
Summary: This paper provides an experience report on a remote framework for early undergraduate research experiences focused on sensing humans computationally. The framework consists of three components: team-based research cycle, professional development activities, and cohort-networking programming. The authors discuss the challenges and opportunities of remote training and evaluate its effectiveness through reflections and interviews.
PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1
(2022)
Proceedings Paper
Computer Science, Cybernetics
Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, Cecilia Alm
Summary: This study examines the impact of human-robot interaction on Theory of Mind assessments, focusing on the effectiveness of using robot facilitators in future human-subject research.
HUMAN-COMPUTER INTERACTION: TECHNOLOGICAL INNOVATION, PT II
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Angela Saquinaula, Adriel Juarez, Joe Geigel, Reynold Bailey, Cecilia O. Alm
Summary: This study explores the extent to which empathetic reactions are elicited when subjects view 3D motion-capture driven avatar faces compared to viewing human faces. Results show no sign of facial mimicry, only slight mimicry of facial movements without consistency. Participants tended to empathize with avatars when they could identify the stimulus' emotion adequately. Increasing avatar realism negatively impacted the subjects' feelings towards the stimuli.
2022 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Robik Shrestha, Kushal Kafle, Christopher Kanan
Summary: A critical problem in deep learning is that systems learn inappropriate biases, resulting in their inability to perform well on minority groups. Multiple algorithms have been developed to mitigate bias but their effectiveness remains unclear.
2022 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. Van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost Van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni
Summary: In this work, Avalanche, an open-source end-to-end library based on PyTorch, is proposed for continual learning research, aiming to provide a shared and collaborative codebase for fast prototyping, training, and reproducible evaluation of continual learning algorithms.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Nikhil Kaushik, Reynold Bailey, Alexander Ororbia, Cecilia O. Alm
Summary: Confusion is a complex emotional experience involving both cognitive and emotional components, and it may be less obvious than core emotions like anger or sadness. An online data collection study was conducted to induce confusion in spontaneous conversations, with results suggesting that the tasks successfully elicited naturalistic confusion, contributing towards automated confusion recognition.
2021 9TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION WORKSHOPS AND DEMOS (ACIIW)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Tyler L. Hayes, Christopher Kanan
Summary: Continual learning in neural networks for analogical reasoning has been studied, with experimental baselines, protocols, and transfer metrics established to evaluate performance on tests like Raven's Progressive Matrices. The use of selective replay has shown significant benefits for the RPM task compared to random replay in mitigating catastrophic forgetting.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021
(2021)
Meeting Abstract
Oncology
J. A. Retamero, P. Raciti, P. Hamilton, B. Rothrock, J. Sue, M. Horton, C. Kanan
JOURNAL OF PATHOLOGY
(2021)
Meeting Abstract
Oncology
M. Hanna, M. Lee, A. Bozkurt, P. Hamilton, R. Godrich, A. Casson, P. Raciti, J. Sue, J. Viret, D. Lee, L. Grady, B. Rothrock, B. Dogdas, T. Fuchs, J. Reis-Filho, C. Kanan
JOURNAL OF PATHOLOGY
(2021)
Article
Health Care Sciences & Services
Usman Mahmood, Robik Shrestha, David D. B. Bates, Lorenzo Mannelli, Giuseppe Corrias, Yusuf Emre Erdi, Christopher Kanan
Summary: Artificial intelligence has been successful in solving problems in machine perception. In radiology, AI systems are rapidly evolving and progress in guiding treatment decisions, diagnosing, localizing disease on medical images, and improving radiologists' efficiency. Conducting analytical validation and clinical validation studies are critical components to deploy AI in radiology.
FRONTIERS IN DIGITAL HEALTH
(2021)
Meeting Abstract
Medicine, Research & Experimental
Matthew Hanna, Matthew Lee, Alican Bozkurt, Ran Godrich, Adam Casson, Patricia Raciti, Jillian Sue, Julian Viret, Donghun Lee, Leo Grady, Brandon Rothrock, Belma Dogdas, Thomas Fuchs, Jorge Reis-Filho, Christopher Kanan
LABORATORY INVESTIGATION
(2021)