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Journal ArticleDOI

Human-Centred Intelligent Human Computer Interaction (HCI²): how far are we from attaining it?

TLDR
How far the authors are to the goal of human-centred computing and Human-Centred Intelligent Human-Computer Interaction (HCI2) that can understand and respond to multimodal human communication is discussed.
Abstract
A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. To realise this prediction, next-generation computing should develop anticipatory user interfaces that are human-centred, built for humans and based on naturally occurring multimodal human communication. These interfaces should transcend the traditional keyboard and mouse and have the capacity to understand and emulate human communicative intentions as expressed through behavioural cues, such as affective and social signals. This article discusses how far we are to the goal of human-centred computing and Human-Centred Intelligent Human-Computer Interaction (HCI2) that can understand and respond to multimodal human communication.

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Citations
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Journal ArticleDOI

Vision based hand gesture recognition for human computer interaction: a survey

TL;DR: An analysis of comparative surveys done in the field of gesture based HCI and an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it under different key parameters are provided.
Book

Social Signal Processing

TL;DR: It is argued that next-generation computing needs to include the essence of social intelligence - the ability to recognize human social signals and social behaviours like turn taking, politeness, and disagreement - in order to become more effective and more efficient.
Journal ArticleDOI

Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks

TL;DR: This paper proposes to learn affect-salient features for SER using convolutional neural networks (CNN), and shows that this approach leads to stable and robust recognition performance in complex scenes and outperforms several well-established SER features.
Journal ArticleDOI

Automatic, Dimensional and Continuous Emotion Recognition

TL;DR: Recent advances in dimensional and continuous affect modeling, sensing, and automatic recognition from visual, audio, tactile, and brain-wave modalities are explored.
Journal ArticleDOI

Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing

TL;DR: This is the first survey of the domain that jointly considers its three major aspects, namely, modeling, analysis, and synthesis of social behavior, which investigates laws and principles underlying social interaction, and explores approaches for automatic understanding of social exchanges recorded with different sensors.
References
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Journal ArticleDOI

Face recognition: A literature survey

TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Journal ArticleDOI

Detecting faces in images: a survey

TL;DR: In this article, the authors categorize and evaluate face detection algorithms and discuss relevant issues such as data collection, evaluation metrics and benchmarking, and conclude with several promising directions for future research.
Book

Handbook of Emotions

TL;DR: In this paper, the authors discuss the role of emotion in the development of the human brain and its role in human emotion processing, and propose a framework to understand the relationship between human emotion and the brain.
Journal ArticleDOI

The chameleon effect: The perception–behavior link and social interaction.

TL;DR: The authors suggest that the mechanism involved is the perception-behavior link, the recently documented finding that the mere perception of another's behavior automatically increases the likelihood of engaging in that behavior oneself.
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