Human Perception of Visual Information: Psychological and Computational Perspectives

Recent advancements in psychology and machine learning have led to a better understanding of the psychological underpinnings of subjective visual information. This book combines perspectives from psychology and machine learning to showcase a unified understanding of how images and videos influence high-level visual perception, particularly interestingness, affective values, emotions, aesthetic values, memorability, novelty, complexity, visual composition, and stylistic attributes.

Format: Paperback / softback
Length: 292 pages
Publication date: 19 December 2022
Publisher: Springer Nature Switzerland AG

In recent years, remarkable strides have been made in our understanding of the psychological foundations of subjective qualities of visual information, including aesthetics, memorability, and induced emotions. Simultaneously, computational models of objective visual properties, such as semantic labeling and geometric relationships, have achieved significant breakthroughs through the utilization of cutting-edge machine learning techniques and extensive data collection. While progress has been limited in exploring how these breakthroughs can be harnessed to enhance computational modeling of subjective visual properties, the time is now ripe to explore the potential for mutual enrichment and progress in these fields.

This book brings together perspectives from psychology and machine learning to present a novel and unified understanding of how images and videos influence high-level visual perception, particularly in terms of interestingness, affective values, emotions, aesthetic values, memorability, novelty, complexity, visual composition, and stylistic attributes, as well as creativity. These human-based metrics hold immense significance for a wide array of current applications, spanning content retrieval and search, storytelling, targeted advertising, education and learning, and content filtering. Existing literature already explores the psychological aspects of these notions or investigates potential correlations between them. Furthermore, attempts have been made to build computational models capable of predicting these notions, employing state-of-the-art machine learning techniques. However, the performance of these models indicates that there is still room for improvement, as the tasks involved are inherently complex and multifaceted, requiring further refinement and development.

By combining insights from psychology and machine learning, this book aims to bridge the gap between these two disciplines and provide a comprehensive framework for understanding the interplay between images and videos in shaping visual perception. It offers valuable insights for researchers, practitioners, and industry professionals seeking to leverage the power of visual information in various domains. The chapters in this book are organized in a way that allows for a seamless flow of information, making it accessible to a broad audience. Each chapter begins with an introduction that provides a background on the relevant topic and highlights the significance of the research being presented. The subsequent sections delve into the theoretical foundations, empirical studies, and computational models that contribute to our understanding of the interplay between images and videos in shaping visual perception.

Furthermore, the book includes case studies and practical applications that demonstrate the practical implications of the research findings. These case studies showcase how images and videos can be effectively designed and manipulated to evoke specific emotions, enhance storytelling, improve user engagement, and enhance marketing strategies. By integrating psychological principles with machine learning techniques, this book provides a roadmap for developing more effective and personalized visual communication strategies that resonate with audiences.

In conclusion, the field of visual perception has witnessed significant advancements in recent years, driven by the convergence of psychology and machine learning. This book combines perspectives from both disciplines to present a comprehensive understanding of how images and videos influence high-level visual perception, particularly in terms of interestingness, affective values, emotions, aesthetic values, memorability, novelty, complexity, visual composition, and stylistic attributes, as well as creativity. By exploring the mutual enrichment and progress between these fields, this book aims to pave the way for developing more effective and personalized visual communication strategies that resonate with audiences and drive positive outcomes in various domains.

Weight: 468g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030814670
Edition number: 1st ed. 2022