相关论文: edBB: Biometrics and Behavior for Assessing Remote…
We introduce a novel multimodal mobile database called HuMIdb (Human Mobile Interaction database) that comprises 14 mobile sensors acquired from 600 users. The heterogeneous flow of data generated during the interaction with the smartphones…
Attention is a key factor for successful learning, with research indicating strong associations between (in)attention and learning outcomes. This dissertation advanced the field by focusing on the automated detection of attention-related…
Active authentication is the problem of continuously verifying the identity of a person based on behavioral aspects of their interaction with a computing device. In this study, we collect and analyze behavioral biometrics data from…
We present results from a set of experiments in this pilot study to investigate the causal influence of user activity on various environmental parameters monitored by occupant carried multi-purpose sensors. Hypotheses with respect to each…
Utilization of the Internet in our everyday lives has made us vulnerable in terms of privacy and security of our data and systems. Therefore, there is a pressing need to protect our data and systems by improving authentication mechanisms,…
Student disengagement in online learning has become a critical challenge, particularly post-pandemic. This review explores deep learning techniques used to detect disengagement, emphasizing computer vision and affective computing as…
Recent research has shown the possibility of using smartphones' sensors and accessories to extract some behavioral attributes such as touch dynamics, keystroke dynamics and gait recognition. These attributes are known as behavioral…
Analyzing student behavior in educational scenarios is crucial for enhancing teaching quality and student engagement. Existing AI-based models often rely on classroom video footage to identify and analyze student behavior. While these…
Automatic analysis of teacher and student interactions could be very important to improve the quality of teaching and student engagement. However, despite some recent progress in utilizing multimodal data for teaching and learning…
In this paper, we introduce two remote extended reality (XR) research methods that can overcome the limitations of lab-based controlled experiments, especially during the COVID-19 pandemic: (1) a predictive model-based task analysis and (2)…
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness, unobtrusiveness, and ecological validity.…
This paper presents a novel database comprising representations of five different biometric characteristics, collected in a mobile, unconstrained or semi-constrained setting with three different mobile devices, including characteristics…
Online remote learning has certain advantages, such as higher flexibility and greater inclusiveness. However, a caveat is the teachers' limited ability to monitor student interaction during an online class, especially while teachers are…
We present GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking (ET) dataset collected at 250 Hz with an ET-enabled virtual-reality (VR) headset. GazeBaseVR comprises 5,020 binocular recordings from a diverse population of 407…
Learning difficulties pose significant challenges for students, impacting their academic performance and overall educational experience. These difficulties could sometimes put students into a downward spiral that lack of educational…
College students experience many stressors, resulting in high levels of anxiety and depression. Wearable technology provides unobtrusive sensor data that can be used for the early detection of mental illness. However, current research is…
The aim of this study was to predict university students' learning performance using different sources of data from an Intelligent Tutoring System. We collected and preprocessed data from 40 students from different multimodal sources:…
The automated analysis of human behaviour provides many opportunities for the creation of interactive systems and the post-experiment investigations for user studies. Commodity depth cameras offer reasonable body tracking accuracy at a low…
Hand gesture understanding is essential for several applications in human-computer interaction, including automatic clinical assessment of hand dexterity. While deep learning has advanced static gesture recognition, dynamic gesture…
Webcam eye tracking for the collection of gaze data in the context of user studies is convenient - it can be used in remote tests where participants do not need special hardware. The approach has strong limitations, especially regarding the…