Human Perception of Visual Information : Psychological and Computational Perspectives / edited by Bogdan Ionescu, Wilma A. Bainbridge, Naila Murray.

Format:

Book

Contributor:

Ionescu, Bogdan, Editor.

Bainbridge, Wilma A., Editor.

Murray, Naila, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Image processing.

Cognitive psychology.

User interfaces (Computer systems).

Human-computer interaction.

Image Processing.

Cognitive Psychology.

User Interfaces and Human Computer Interaction.

Local Subjects:

Image Processing.

Cognitive Psychology.

User Interfaces and Human Computer Interaction.

Physical Description:

1 online resource (IX, 292 pages) : 69 illustrations, 56 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

Recent years have witnessed important advancements in our understanding of the psychological underpinnings of subjective properties of visual information, such as aesthetics, memorability, or induced emotions. Concurrently, computational models of objective visual properties such as semantic labelling and geometric relationships have made significant breakthroughs using the latest achievements in machine learning and large-scale data collection. There has also been limited but important work exploiting these breakthroughs to improve computational modelling of subjective visual properties. The time is ripe to explore how advances in both of these fields of study can be mutually enriching and lead to further progress. This book combines perspectives from psychology and machine learning to showcase a new, unified understanding of how images and videos influence high-level visual perception - particularly interestingness, affective values and emotions, aesthetic values, memorability, novelty, complexity, visual composition and stylistic attributes, and creativity. These human-based metrics are interesting for a very broad range of current applications, ranging from content retrieval and search, storytelling, to targeted advertising, education and learning, and content filtering. Work already exists in the literature that studies the psychological aspects of these notions or investigates potential correlations between two or more of these human concepts. Attempts at building computational models capable of predicting such notions can also be found, using state-of-the-art machine learning techniques. Nevertheless their performance proves that there is still room for improvement, as the tasks are by nature highly challenging and multifaceted, requiring thought on both the psychological implications of the human concepts, as well as their translation to machines.

Contents:

Preface

Chapter 1

The Ingredients of Scenes That Affect Object Search and Perception

Chapter 2

Exploring Deep Fusion Ensembling for Automatic Visual Interestingness Prediction

Chapter 3

Affective Perception: The Power is in the Picture

Chapter 4

Computational Emotion Analysis From Images: Recent Advances and Future Directions

Chapter 5

The Interplay Of Objective And Subjective Factors In Empirical Aesthetics

Chapter 6

Advances and Challenges in Computational Image Aesthetics

Chapter 7

Shared Memories Driven by the Intrinsic Memorability of Items

Chapter 8

Memorability: an Image-computable Measure of Information Utility

Chapter 9

The Influence of Low

and Mid-Level Visual Features on the Perception of Streetscape Qualities

Chapter 10

Who Sees What? Examining Urban Impressions in Global South Cities.

Other Format:

Printed edition:

ISBN:

978-3-030-81465-6

9783030814656

Access Restriction:

Restricted for use by site license.