13,157 research outputs found
A Mimetic Strategy to Engage Voluntary Physical Activity In Interactive Entertainment
We describe the design and implementation of a vision based interactive
entertainment system that makes use of both involuntary and voluntary control
paradigms. Unintentional input to the system from a potential viewer is used to
drive attention-getting output and encourage the transition to voluntary
interactive behaviour. The iMime system consists of a character animation
engine based on the interaction metaphor of a mime performer that simulates
non-verbal communication strategies, without spoken dialogue, to capture and
hold the attention of a viewer. The system was developed in the context of a
project studying care of dementia sufferers. Care for a dementia sufferer can
place unreasonable demands on the time and attentional resources of their
caregivers or family members. Our study contributes to the eventual development
of a system aimed at providing relief to dementia caregivers, while at the same
time serving as a source of pleasant interactive entertainment for viewers. The
work reported here is also aimed at a more general study of the design of
interactive entertainment systems involving a mixture of voluntary and
involuntary control.Comment: 6 pages, 7 figures, ECAG08 worksho
Emotions in context: examining pervasive affective sensing systems, applications, and analyses
Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; âsensingâ, âanalysisâ, and âapplicationâ. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing
Internet: Culture Diversity and Unification
Culture specifics of the Internet usage is analysed. The analysis done is a preliminary work for the application of the socio-historical theory of human mental development. The practice of the Internet usage is ambigious as it gives rise to both the unification and the diversity. The parameters analysed include the techniques of the hypertexts browsing,\ud
and the status/position/rank of the communicators - its influence on holding the floor and turntaking rules, the ways the emotions are expressed while Internet communication, and the way the English language serves the functions of world-wide medium
Enhancing Students' Metacognition via AI-Driven Educational Support Systems
As the penetration of digital technology deepens and the demands for educational modernization grow, attention is increasingly being drawn towards the application of artificial intelligence (AI) in the field of education. Especially in educational practice, the optimization of studentsâ learning experiences and the enhancement of their metacognitive abilities through AI technology have captivated the interest of numerous educators and scholars. Metacognition, which represents a core skill in student self-regulation and self-management, has a significant impact on student learning outcomes and quality. However, current educational support systems primarily rely upon traditional methods of data collection and analysis, which have limitations in terms of real-time responsiveness, granularity, and comprehensiveness. The present research aims to investigate the integration of AI technology with a specific focus on the learning process through educational support systems and the development of a cooperative teaching interaction model. This will ultimately enhance the development of studentsâ metacognitive abilities more effectively
Enhancing Facial Emotion Recognition with a Modified Deep Convolutional Neural Network
Understanding and predicting human character traits play a crucial role in various domains ranging from psychology to human resources. With the advent of artificial intelligence (AI) and deep learning algorithms, researchers have explored the potential of analyzing facial images to predict human character traits accurately. In this paper, we present a comprehensive study of the application of AI techniques for human character recognition. We review the existing literature on facial image analysis, AI algorithms, and personality prediction. Furthermore, we propose a methodology that leverages deep learning and convolutional neural networks (CNNs) to extract meaningful features from facial images. Our experiments demonstrate the effectiveness of our approach in accurately predicting character traits and showcasing promising results using small-scale datasets. We discuss the implications of our findings in psychology, human resources, and personalized user experiences. Additionally, ethical considerations, such as privacy and bias, are addressed. This research contributes to the growing field of AI-driven character recognition, providing insights for further advancements and practical applications in understanding human behavio
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