System and Application for Happiness

Session Chairs

Anchao Tsai, Tajen University, Taiwan

Tawen Kuan, National Cheng Kung University, Taiwan

Brief Introduction on the Session

The special session highly welcomes the innovative and creative research on state-of-the-art framework, system and application based on happiness informatics to recognize the human positive/negative emotion, expression, speech, language through the human audio-visual cues and physiology signals (such as, brain wave and brain region), also discusses the appropriate feedback strategy based on the recognized results to promote the human happiness. The research works or topics including, the happiness acoustic recognition, the happiness semantic recognition, the laughter detection or recognition, the positivity or negative facial expression/ body behavior/gesture recognition, the fMRI for happiness brain region recognition, the EEG for happiness brain wave recognition and the happiness feedback strategy etc. are welcome for this special session submission.

Building Bridges between Technology and Wellbeing

Session Chair

Chiyue Chiu, The Chinese University of Hong Kong, Hong Kong

Brief Introduction on the Session

To be announced soon

Social Signal and Information Processing for Emotional Well-being

Session Chair

Chunghsien Wu, National Cheng Kung University, Taiwan

Brief Introduction on the Session

In today’s world, social interaction undoubtedly plays an important role in our daily life. Toward harmonious human-computer interaction interface, automated analysis and processing of social signals has attracted increasing attention from the researchers in multidisciplinary research fields. Emotion expressions provide information about the interaction partners’ disposition and the situation as such. That is, emotions serve as social signals. Acknowledging this role of emotions, this special session brings together research that illustrates how both person perception and situational understanding can be derived from emotional expressions and the modulation of this process through context. Technologies for processing daily activities from social signals including speech, text and social media have expanded the interaction modalities between humans and computer-supported communicational artifacts. In this special session, papers covering theoretical and practical work offering new and broad views of the latest research in data analysis and processing of the social media will be presented. The papers will span a variety of theoretical background and applications ranging from emoticon recommendation, topic modeling, emotion expression in social media, affective episodes for daily activity analysis, emotion recognition of affective speech to related applications on these modalities.

Human Behavior and Activities Tracking

Session Chair

Dong Xuan, The Ohio State University, USA

Brief Introduction on the Session

Human behavior and activities tracking is important for various applications such as senior healthcare, facilities management, and public safety. For examples, accurately and rapidly detecting falls among the elderly, growing queues outside stadiums during concerts, and criminal activities in public areas are desirable for these respective applications.

However, this task is challenging. Humans' motions can be unpredictable in areas to be monitored. Sensors such as video cameras are subject to noise and environmental variation such as changing illumination. Other sensors such as mobile devices have limited resources such as battery life that hinder feasible computation. Sensors generate an enormous volume of data to be stored and processed. Often, noisy data from several types of sensors needs to be fused for human activity analysis. In dangerous situations such as elders' falls or ongoing crimes, sensor systems need to analyze human activities subject to tight timing constraints. Detecting activities of crowds of people amplify the challenges as sensors can confuse individuals in the crowd with varying activities.

This session welcomes research in human behavior and activity tracking addressing challenges such as those above.

Eco-friendly Computing

Session Chair

Ichiro Satoh, National Institute of Informatics, Japan

Brief Introduction on the Session

To be announced soon

Community Empowerment and Hedonic/Eudaimonic Wellbeing

Session Chair

Shyhnan Liou, National Cheng Kung University, Taiwan

Brief Introduction on the Session

In the section of “Community Empowerment and Hedonic/Eudaimonic Wellbeing”, we adopt two distinctive approaches to study technology and wellbeing: 1) community based research, which is potential to explore the holist life in context. With contextualized cultural-social and spatial influence, allow us to examine the naturalistic life; 2) Interdisciplinary integration. The research reported in this section are interdisciplinary and cross level which include philosophically conceptual reflection, distinction of hedonic/eudaimonic wellbeing indicators, as well as mobile-based communication technology on well-being, and service design and community care system. With this “diverse in harmony” approach opens the opportunity to revise the issue of measure and development of the Hedonic/Eudaimonic Wellbeing in design and practice in empowering community.

Data Analysis for Mental Health

Session Chair

Sriram Chellappan, University of South Florida, USA

Brief Introduction on the Session

This session emphasizes on data analytics for mental health and wellbeing of society across all age groups from the perspective of technology usage. In the last decade, digital data generated from devices like computers, smartphones, and the Internet are massive in scale, context, modality and dimensionality. Mining these sources of data for mental health and wellbeing is the principal focus of this session. We are interested in all aspects of data storage, data retrieval, data mining techniques, and machine learning algorithms centered on digital data and its interplay with mental health. These include leveraging digital data for deriving insights into mental health of an increasingly digital population from multiple perspectives into assessing behavior (like mood, sociability, abnormalities etc.), predicting mental illnesses (like depression, stress, anxiety etc.), gauging cognitive abilities with applications to treating diseases like Alzheimer’s and Parkinson’s and more. Recent research has shown that deriving such insights on mental health are increasingly achievable using data from Computer Usage, Social Media, Wearable and Smartphone sensors. This session provides a platform to further such studies. We are also interested in emerging digital technologies and algorithms that demonstrate applicability to improve emotional and cognitive abilities across populations.

Audio/Visual Techniques for Immersive Communication

Session Chairs

Zhonghua Fu and Lei Xie, Northwestern Polytechnic University, China

Brief Introduction on the Session

The immersive communication aims at providing an immersive “in-the-same-room” experience for the communicators involved and enables natural interactions among people who are geographically distributed via 3D audio/visual technologies. Recently, various research communities have been studying on audio/visual processing for immersive environments, including 3D audio rendering, audio/speech/video capture/synthesis/recognition/enhancement, 3D visual construction and multimodal multimedia interaction. The proliferation of tele-presence systems, which is a form of immersive communication enabling effective remote collaboration through realistic audio and video reconstruction of participants and their environments, demonstrates the important of immersive audio/visual communication.