One of the defining attributes of the human species is sophisticated communication, for which facial expressions are crucial. Traditional research has so far mainly investigated a minority of 6 basic emotional expressions displayed as pictures. Despite the important insights of this approach, its ecological validity is limited: facial movements express more than emotions, and facial expressions are more than just pictures. The objective of the present thesis is therefore to improve the understanding of facial expression recognition by investigating the internal representations of a large range of facial expressions, displayed both as static pictures and as dynamic videos. To this end, it was necessary to develop and validate a new facial expression database which includes 20.000 stimuli of 55 expressions (study 1). Perceptual representations of the six basic emotional expressions were found previously to rely on evaluation of valence and arousal; study 2 showed that this evaluation generalises to many more expressions, particularly when displayed as videos. While it is widely accepted that knowledge influences perception, how these are linked is largely unknown; study 3 investigated this question by asking how knowledge about facial expressions, instantiated as conceptual representations, relates to perceptual representations of these expressions. A strong link was found which changed with the kind of expressions and the type of display. In probably the most extensive behavioural studies (with regards to the number of facial expressions used) to date, this thesis suggests that there are commonalities but also differences in processing of emotional and of other types of facial expressions. Thus, to understand facial expression processing, one needs to consider more than the 6 basic emotional expressions. These findings outline first steps towards a new domain in facial expression research, which has implications for a number of research and application fields where facial expressions play a role, ranging from social, developmental, and clinical psychology to computer vision and affective computing research.

Our body is central to what we define as our self. The mental representation of our physical appearance, often called body image, can have a great influence on our psychological health. Given the increase in body mass index worldwide and the societal pressure to conform to body ideals, it is important to gain a better understanding of the nature of body representations and factors that play a role in body size estimation tasks. This doctoral thesis takes a multifaceted approach for investigating the role of different visual cues in the estimation of own body size and shape by using a variety of experimental methods and novel state-of-the-art computer graphics methods. Two visual cues were considered: visual perspective and identity cues in the visual appearance of a body (shape, and color-information), as well as their interactions with own body size and gender. High ecological validity was achieved by testing body size estimation in natural settings, when looking into a mirror, and by generating biometrically plausible virtual bodies based on 3D body scans and statistical body models, and simulating real-world scenarios in immersive virtual reality.

Humans always wanted to go faster and higher than their own legs could carry them. This led them to invent numerous types of vehicles to move fast over land, water and air. As training how to handle such vehicles and testing new developments can be dangerous and costly, vehicle motion simulators were invented. Motion-based simulators in particular, combine visual and physical motion cues to provide occupants with a feeling of being in the real vehicle. While visual cues are generally not limited in amplitude, physical cues certainly are, due to the limited simulator motion space. A motion cueing algorithm (MCA) is used to map the vehicle motions onto the simulator motion space. This mapping inherently creates mismatches between the visual and physical motion cues. Due to imperfections in the human perceptual system, not all visual/physical cueing mismatches are perceived. However, if a mismatch is perceived, it can impair the simulation realism and even cause simulator sickness. For MCA design, a good understanding of when mismatches are perceived, and ways to prevent these from occurring, are therefore essential. In this thesis a data-driven approach, using continuous subjective measures of the time-varying Perceived Motion Incongruence (PMI), is adopted. PMI in this case refers to the effect that perceived mismatches between visual and physical motion cues have on the resulting simulator realism. The main goal of this thesis was to develop an MCA-independent off-line prediction method for time-varying PMI during vehicle motion simulation, with the aim of improving motion cueing quality. To this end, a complete roadmap, describing how to measure and model PMI and how to apply such models to predict and minimize PMI in motion simulations is presented. Results from several human-in-the-loop experiments are used to demonstrate the potential of this novel approach.

This edition contains over 460 additional references and the treatment of visual psychology in the early chapters has been extensively revised.

This eBook aims to deepen our understanding of emotional communication by introducing “dynamic” perspectives. Facial and bodily expressions of emotion functions as indispensable communicative signals for human beings. People decode the emotional information conveyed by facial/bodily expressions and use this to coordinate cooperative or competitive social relationships. Experimental psychological research has long investigated these important means of emotional communication. However, this was typically done by using static stimuli of facial/bodily expressions to assess the detection and interpretation of emotions. This paradigm was also adopted in neuropsychological, neurophysiological, and neuroimaging studies. Although researchers accumulated valuable information regarding the psychological and neural mechanisms underlying these processes, the static nature of the stimuli may have resulted in important phenomena remaining unexamined. Recently, scientists have begun to explore dynamic emotional communication, in particular by using dynamic facial/bodily expressions of emotion, instead of static photographs, as stimuli. This is having important consequences for emotion research. As dynamic emotional expressions have increased ecological validity and as there are differences in the visual processing of dynamic and static information, a host of novel aspects of the psychological and neural processing of emotional expressions have been elucidated. For example, it has been shown that motor resonance and the recruitment of motor areas are fundamental to dynamic emotional communication. Researchers have also started to investigate the encoding of dynamic emotional interactions and have clarified the messages embedded in the temporal aspects and the patterns of reciprocal inter-individual coordination. Moreover, investigations of dynamic emotional communication have identified heretofore unrecognized impairments in the social functioning of individuals with psychiatric disorders, such as autism spectrum disorder and schizophrenia.

This volume synthesizes social, cognitive, ecological, evolutionary, & neuroscience research, showing that the way in which people perceive the world changes with their cognitions, emotions, goals, motivations, culture, & other factors traditionally considered exclusive to social, personality, & cognitive psychology.

The two volume set, consisting of LNCS 7728 and 7729, contains the carefully reviewed and selected papers presented at the nine workshops that were held in conjunction with the 11th Asian Conference on Computer Vision, ACCV 2012, in Daejeon, South Korea, in November 2012. From a total of 310 papers submitted, 78 were selected for presentation. LNCS 7728 contains the papers selected for the International Workshop on Computer Vision with Local Binary Pattern Variants, the Workshop on Computational Photography and Low-Level Vision, the Workshop on Developer-Centered Computer Vision, and the Workshop on Background Models Challenge. LNCS 7729 contains the papers selected for the Workshop on e-Heritage, the Workshop on Color Depth Fusion in Computer Vision, the Workshop on Face Analysis, the Workshop on Detection and Tracking in Challenging Environments, and the International Workshop on Intelligent Mobile Vision.

Neuroimaging Personality, Social Cognition, and Character covers the science of combining brain imaging with other analytical techniques for use in understanding cognition, behavior, consciousness, memory, language, visual perception, emotional control, and other human attributes. Multidimensional brain imaging research has led to a greater understanding of character traits such as honesty, generosity, truthfulness, and foresight previously unachieved by quantitative mapping. This book summarizes the latest brain imaging research pertaining to character with structural and functional human brain imaging in both normal individuals and those with brain disease or disorder, including psychiatric disorders.By reviewing and synthesizing the latest structural and functional brain imaging research related to character, this book situates itself into the larger framework of cognitive neuroscience, psychiatric neuroimaging, related fields of research, and a wide range of academic fields, such as politics, psychology, medicine, education, law, and religion. - Provides a novel innovative reference on the emerging use of neuroimaging to reveal the biological substrates of character, such as optimism, honesty, generosity, and others - Features chapters from leading physicians and researchers in the field - Contains full-color text that includes both an overview of multiple disciplines and a detailed review of modern neuroimaging tools as they are applied to study human character - Presents an integrative volume with far-reaching implications for guiding future imaging research in the social, psychological and medical sciences, and for applying these findings to a wide range of non-clinical disciplines such as law, politics, and religion - Connects brain structure and function to human character and integrates modern neuroimaging techniques and other research methods for this purpose

Brain Mapping: A Comprehensive Reference, Three Volume Set offers foundational information for students and researchers across neuroscience. With over 300 articles and a media rich environment, this resource provides exhaustive coverage of the methods and systems involved in brain mapping, fully links the data to disease (presenting side by side maps of healthy and diseased brains for direct comparisons), and offers data sets and fully annotated color images. Each entry is built on a layered approach of the content – basic information for those new to the area and more detailed material for experienced readers. Edited and authored by the leading experts in the field, this work offers the most reputable, easily searchable content with cross referencing across articles, a one-stop reference for students, researchers and teaching faculty. Broad overview of neuroimaging concepts with applications across the neurosciences and biomedical research Fully annotated color images and videos for best comprehension of concepts Layered content for readers of different levels of expertise Easily searchable entries for quick access of reputable information Live reference links to ScienceDirect, Scopus and PubMed