This book provides comprehensive, authoritative surveys covering the modeling, automatic detection, analysis, and synthesis of nonverbal social signals.

This book contains papers invited after the First International Workshop on Mobile Social Signal Processing, MSSP 2010, held in Lisbon, Portugal, in September 2010. The 9 revised papers included in this volume represent the diversity of two fields of research, Mobile HCI and Social Signal Processing and areas of overlap. They cover a wide range of topics spanning from approaches for effective interaction with mobile and wearable devices to modelling, analysis and synthesis of nonverbal behaviour in human-human and human-machine interactions.

Powerful and economic sensors such as high definition cameras and corresponding recognition software have become readily available, e.g. for face and motion recognition. However, designing user interfaces for robots, phones and computers that facilitate a seamless, intuitive, and apparently effortless communication as between humans is still highly challenging. This has shifted the focus from developing ever faster and higher resolution sensors to interpreting available sensor data for understanding social signals and recognising users' intentions. Psychologists, Ethnologists, Linguists and Sociologists have investigated social behaviour in human-human interaction. But their findings are rarely applied in the human-robot interaction domain. Instead, robot designers tend to rely on either proof-of-concept or machine learning based methods. In proving the concept, developers effectively demonstrate that users are able to adapt to robots deployed in the public space. Typically, an initial period of collecting human-robot interaction data is used for identifying frequently occurring problems. These are then addressed by adjusting the interaction policies on the basis of the collected data. However, the updated policies are strongly biased by the initial design of the robot and might not reflect natural, spontaneous user behaviour. In the machine learning approach, learning algorithms are used for finding a mapping between the sensor data space and a hypothesised or estimated set of intentions. However, this brute-force approach ignores the possibility that some signals or modalities are superfluous or even disruptive in intention recognition. Furthermore, this method is very sensitive to peculiarities of the training data. In sum, both methods cannot reliably support natural interaction as they crucially depend on an accurate model of human intention recognition. Therefore, approaches to social robotics from engineers and computer scientists urgently have to be informed by studies of intention recognition in natural human-human communication. Combining the investigation of natural human behaviour and the design of computer and robot interfaces can significantly improve the usability of modern technology. For example, robots will be easier to use by a broad public if they can interpret the social signals that users spontaneously produce for conveying their intentions anyway. By correctly identifying and even anticipating the user's intention, the user will perceive that the system truly understands her/his needs. Vice versa, if a robot produces socially appropriate signals, it will be easier for its users to understand the robot's intentions. Furthermore, studying natural behaviour as a basis for controlling robots and other devices results in greater robustness, responsiveness and approachability. Thus, we welcome submissions that (a) investigate how relevant social signals can be identified in human behaviour, (b) investigate the meaning of social signals in a specific context or task, (c) identify the minimal set of intentions for describing a context or task, (d) demonstrate how insights from the analysis of social behaviour can improve a robot's capabilities, or (e) demonstrate how a robot can make itself more understandable to the user by producing more human-like social signals.

This book constitutes the thoroughly refereed post-workshop proceedings of the First IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction (MPRSS2012), held in Tsukuba, Japan in November 2012, in collaboration with the NLGD Festival of Games. The 21 revised papers presented during the workshop cover topics on facial expression recognition, audiovisual emotion recognition, multimodal Information fusion architectures, learning from unlabeled and partially labeled data, learning of time series, companion technologies and robotics.

Designing robots with socio-emotional skills is a challenging research topic still in its infancy. These skills are important for robots to be able to provide not only physical, but also social support to human users, and to engage in and sustain long-term interactions with them in a variety of application domains that require human-robot interaction, including healthcare, education, entertainment, manufacturing, and many others. The availability of commercial robotic platforms and developments in collaborative academic research provide us a positive outlook, however, the capabilities of current social robots are quite limited. The main challenge is understanding the underlying mechanisms of the humans in responding to and interacting with real life situations, and how to model these mechanisms for the embodiment of naturalistic, human-inspired behaviors via robots. To address this challenge successfully requires an understanding of the essential components of social interaction including nonverbal behavioral cues such as interpersonal distance, body position, body posture, arm and hand gestures, head and facial gestures, gaze, silences, vocal outbursts and their dynamics. To create truly intelligent social robots, these nonverbal cues need to be interpreted to form an understanding of the higher level phenomena including first-impression formation, social roles, interpersonal relationships, focus of attention, synchrony, affective states, emotions, and personality, and in turn defining optimal protocols and behaviors to express these phenomena through robotic platforms in an appropriate and timely manner. Achieving this goal requires the fields of psychology, nonverbal behavior, vision, social signal processing, affective computing, and HRI to constantly interact with one another. This Research Topic aims to foster such interactions and collaborations by bringing together the latest works and developments from across a range of research groups and disciplines working in these fields. The Research Topic is a collection of 14 articles that span across five research themes. Three articles co-authored by Terada and Takeuchi, Jung et al., and Kennedy et al. explore the design of “social and affective cues” for robots and investigate their effects on human-robot interaction. Mirnig et al., Bremner et al., and Strait et al. investigate people’s “perceptions of robots” in different settings and scenarios, such as when robots make errors. Articles by Lee et al., Leite et al., and Heath et al. investigate the factors that shape “dialogic interaction with robots,” such as interaction context. The articles under the theme “social and affective therapy” by Rouaix et al., Rudovic et al., and Matsuda et al. report on how individuals from clinical populations, such as those with dementia, autism, and other pervasive developmental disorders (PDDs), interact with robots in therapeutic scenarios. Finally, Miklósi et al. and Durantin et al. offer “new perspectives in human-robot interaction” with a focus on reframing social interaction and human-robot relationships. We are excited about sharing this rich collection with the scientific community and about its contributions to the human-robot interaction literature.

This book features the second volume of the proceedings of the 9th International Conference of the International Association of Cultural and Digital Tourism (IACuDiT). Held at the Syros Island in Greece in September 2022, the conference's lead theme was ‘Tourism, Travel, and Hospitality in a Smart and Sustainable World’. With a full appreciation of the contributions made by numerous writers toward the progress in tourism research, this book presents a critical academic discourse on sustainable practices in a smart tourism context, stimulating future debates and advancing knowledge and understanding in this critical area of knowledge. It also puts emphasis on the knowledge economy and smart destinations notion. It enacts new modes of tourism management and development and presents chapters on emerging technologies, such as location-based services, Internet of Things, smart cities, mobile services, gamification, digital collections and the virtual visitor, social media, social networking, and augmented reality

The Handbook of Information Security is a definitive 3-volume handbook that offers coverage of both established and cutting-edge theories and developments on information and computer security. The text contains 180 articles from over 200 leading experts, providing the benchmark resource for information security, network security, information privacy, and information warfare.

Personalization is ubiquitous from search engines to online-shopping websites helping us find content more efficiently and this book focuses on the key developments that are shaping our daily online experiences. With advances in the detection of end users’ emotions, personality, sentiment and social signals, researchers and practitioners now have the tools to build a new generation of personalized systems that will really understand the user’s state and deliver the right content. With leading experts from a vast array of domains from user modeling, mobile sensing and information retrieval to artificial intelligence, human-computer interaction (HCI) social computing and psychology, a broad spectrum of topics are covered. From discussing psychological theoretical models and exploring state-of-the-art methods for acquiring emotions and personality in an unobtrusive way, as well as describing how these concepts can be used to improve various aspects of the personalization process and chapters that discuss evaluation and privacy issues. Emotions and Personality in Personalized Systems will help aid researchers and practitioners develop and evaluate user-centric personalization systems that take into account the factors that have a tremendous impact on our decision-making – emotions and personality.

While today's game engines and multi-agent platforms cross-fertilize each other to some extent, the technologies used in these areas are not readily compatible due to some differences in their primary concerns. Where game engines prioritize efficiency and central control, multi-agent platforms focus on agent autonomy and sophisticated communication capabilities. This volume gives an overview of the current state of the art for people wishing to combine agent technology with (serious) games. This state-of-the-art survey contains a collection of papers presented at AGS 2010; the Second International Workshop on Agents for Games and Simulations, held on May 10, 2010, in Toronto, as well as extended versions of papers from other workshops and from the AAMAS conference. The 14 papers are organized in three topical sections focusing on architectures combining agents and game engines, on the training aspects of the games, on social and organizational aspects of games and agents, respectively.