The only textbook to frame cognitive psychology in the context of our everyday lives.Our lives are governed by cognitive processes, whether we are searching for a face in a crowd, driving to work, or learning a second language. Cognition in the Real World brings together expert contributors who explain the processes underlying everyday behaviours.It is set apart from traditional textbooks by being organised by behaviours we are exposed to every day-such as drawing a picture, learning your way around a new city, or deciding how to invest your money. Such activities naturally involve a variety of cognitive functions; by considering thesefunctions in an integrated way, the text provides a complete picture of how behaviours work together, rather than separately.Drawing upon important insights from areas such as developmental psychology and neuroscience, Cognition in the Real World demonstrates how cognitive psychology fits with the broader subjects around it, rather than treating it as an independent topic.With a strong foundation in cognitive theory, framed by an original and engaging real-world approach, the text makes the topics of cognition come alive.

Face recognition technologies (FRTs) have many practical security-related purposes, but advocacy groups and individuals have expressed apprehensions about their use. This report highlights the high-level privacy and bias implications of FRT systems. The authors propose a heuristic with two dimensions -- consent status and comparison type -- to help determine a proposed FRT's level of privacy and accuracy. They also identify privacy and bias concerns.

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.

In everyday life we identify faces regularly and seemingly with great ease. One might assume this to be a straightforward and highly accurate task. However, we are poor at identifying the faces of unfamiliar people, who we have never met before, despite the fact that many important everyday tasks depend on this. Forensic face matching requires the comparison of two face photographs, of a person who is not known to the observer. This seemingly simple task is critical for a wide range of security tasks, such as person identification at airports and borders, passport issuance and renewal, and criminal identification in police investigations. Despite its ubiquity, face matching is highly prone to error, even under conditions that are designed to maximally facilitate this task. For this reason, face matching has been studied extensively in psychology, with the bulk of the research conducted since 2010. Forensic Face Matching provides readers with a wide-ranging, detailed, and critical overview of facial comparison and face matching, providing insights into its application, efficacy, and limitations in occupational settings, and of current scientific knowledge of this task.

This three-volume set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis; image analysis in agriculture; and data mining, information retrieval and applications.