This book integrates a wide range of research topics related to and necessary for the development of proactive, smart, computers in the human interaction loop, including the development of audio-visual perceptual components for such environments; the design, implementation and analysis of novel proactive perceptive services supporting humans; the development of software architectures, ontologies and tools necessary for building such environments and services, as well as approaches for the evaluation of such technologies and services. The book is based on a major European Integrated Project, CHLI (Computers in the Human Interaction Loop), and throws light on the paradigm shift in the area of HCI that rather than humans interactive directly with machines, computers should observe and understand human interaction, and support humans during their work and interaction in an implicit and proactive manner.

This book constitutes the thoroughly refereed joint post-workshop proceedings of two co-located events: the Second International Workshop on Classification of Events, Activities and Relationships, CLEAR 2007, and the 5th Rich Transcription 2007 Meeting Recognition evaluation, RT 2007, held in succession in Baltimore, MD, USA, in May 2007. The workshops had complementary evaluation efforts; CLEAR for the evaluation of human activities, events, and relationships in multiple multimodal data domains; and RT for the evaluation of speech transcription-related technologies from meeting room audio collections. The 35 revised full papers presented from CLEAR 2007 cover 3D person tracking, 2D face detection and tracking, person and vehicle tracking on surveillance data, vehicle and person tracking aerial videos, person identification, head pose estimation, and acoustic event detection. The 15 revised full papers presented from RT 2007 are organized in topical sections on speech-to-text, and speaker diarization.

This book constitutes the thoroughly refereed post-proceedings of the First International CLEAR 2006 Evaluation Campaign and Workshop on Classification of Events, Activities and Relationships for evaluation of multimodal technologies for the perception of humans, their activities and interactions. The workshop was held in the UK in April 2006. The papers were carefully reviewed and selected for inclusion in the book.

This book presents a survey of past and recent developments on human walking in virtual environments with an emphasis on human self-motion perception, the multisensory nature of experiences of walking, conceptual design approaches, current technologies, and applications. The use of Virtual Reality and movement simulation systems is becoming increasingly popular and more accessible to a wide variety of research fields and applications. While, in the past, simulation technologies have focused on developing realistic, interactive visual environments, it is becoming increasingly obvious that our everyday interactions are highly multisensory. Therefore, investigators are beginning to understand the critical importance of developing and validating locomotor interfaces that can allow for realistic, natural behaviours. The book aims to present an overview of what is currently understood about human perception and performance when moving in virtual environments and to situate it relative to the broader scientific and engineering literature on human locomotion and locomotion interfaces. The contents include scientific background and recent empirical findings related to biomechanics, self-motion perception, and physical interactions. The book also discusses conceptual approaches to multimodal sensing, display systems, and interaction for walking in real and virtual environments. Finally, it will present current and emerging applications in areas such as gait and posture rehabilitation, gaming, sports, and architectural design.

With the advance of speech, image and video technology, human-computer interaction (HCI) will reach a new phase.In recent years, HCI has been extended to human-machine communication (HMC) and the perceptual user interface (PUI). The final goal in HMC is that the communication between humans and machines is similar to human-to-human communication. Moreover, the machine can support human-to-human communication (e.g. an interface for the disabled). For this reason, various aspects of human communication are to be considered in HMC. The HMC interface, called a multimodal interface, includes different types of input methods, such as natural language, gestures, face and handwriting characters.The nine papers in this book have been selected from the 92 high-quality papers constituting the proceedings of the 2nd International Conference on Multimodal Interface (ICMI '99), which was held in Hong Kong in 1999. The papers cover a wide spectrum of the multimodal interface.

This book systematically addresses the quantification of quality aspects of multimodal interactive systems. The conceptual structure is based on a schematic view on human-computer interaction where the user interacts with the system and perceives it via input and output interfaces. Thus, aspects of multimodal interaction are analyzed first, followed by a discussion of the evaluation of output and input and concluding with a view on the evaluation of a complete system.

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. - Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios - Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources - Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data