Framing digital image credibility: image manipulation problems, perceptions and solutions

Image manipulation is subverting the credibility of photographs as a whole. Currently there is no practical solution for asserting the authenticity of a photograph. People express their concern about this when asked but continue to operate in a ‘business as usual’ fashion. While a range of digital forensic technologies has been developed to address falsification of digital photographs, such technologies begin with ‘sourceless’ images and conclude with results in equivocal terms of probability, while not addressing the meaning and content contained within the image. It is interesting that there is extensive research into computer-based image forgery detection, but very little research into how we as humans perceive, or fail to perceive, these forgeries when we view them. The survey, eye-gaze tracking experiments and neural network analysis undertaken in this research contribute to this limited pool of knowledge. The research described in this thesis investigates human perceptions of images that are manipulated and, by comparison, images that are not manipulated. The data collected, and their analyses, demonstrate that humans are poor at identifying that an image has been manipulated. I consider some of the implications of digital image manipulation, explore current approaches to image credibility, and present a potential digital image authentication framework that uses technology and tools that exploit social factors such as reputation and trust to create a framework for technologically packaging/wrapping images with social assertions of authenticity, and surfaced metadata information. The thesis is organised into 6 chapters. Chapter 1: Introduction I briefly introduce the history of photography, highlighting its importance as reportage, and discuss how it has changed from its introduction in the early 19th century to today. I discuss photo manipulation and consider how it has changed along with photography. I describe the relevant literature on the subject of image authentication and the use of eye gaze tracking and neural nets in identifying the role of human vision in image manipulation detection, and I describe my area of research within this context. Chapter 2: Literature review I describe the various types of image manipulation, giving examples, and then canvas the literature to describe the landscape of image manipulation problems and extant solutions, namely: • the nature of image manipulation, • investigations of human perceptions of image manipulation, • eye gaze tracking and manipulated images, • known efforts to create solutions to the problem of preserving unadulterated photographic representations and the meanings they hold. Finally, I position my research activities within the context of the literature. Chapter 3: The research I describe the survey and experiments I undertook to investigate attitudes toward image manipulation, research human perceptions of manipulated and unmanipulated images, and to trial elements of a new wrapper-style file format that I call .msci (mobile self-contained image), designed to address image authenticity issues. Methods, results and discussion for each element are presented in both explanatory text and by presentation of papers resulting from the experiments. Chapter 4: Analysis of eye gaze data using classification neural networks I describe pattern classifying neural network analysis applied to selected data obtained from the experiments and the insights this analysis provided into the opaque realm of cognitive perception as seen through the lens of eye gaze. Chapter 5: Discussion I synthesise and discuss the outcomes of the survey and experiments. I discuss the outcomes of this research, and consider the need for a distinction between photographs and photo art. I offer a theoretical formula within which the overall authenticity of an image can be assessed. In addition I present a potential image authentication framework built around the .msci file format, designed in consideration of my investigation of the requirements of the image manipulation problem space and the experimental work undertaken in this research. Chapter 6: Conclusions and future work This thesis concludes with a summary of the outcomes of my research, and I consider the need for future experimentation to expand on the insights gained to date. I also note some ways forward to develop an image authentication framework to address the ongoing problem of image authenticity

An informed community's perception of the impact of digital technology on the credibility of news photography

South African photojournalists’ perception of digital technology’s impact on the credibility of news photographs is investigated in this study. Digital technology has the capabilities to produce “manipulated” photographs that appear realistic and credible. Credibility is dependent on a variety of factors including codes of realism and codes of production, which fit conventional codes of photographic representation. Manipulation is the act of deviating from accepted codes of photographic representation that may jeopardise the credibility of news photography. This thesis proposes a new theoretical framework that encompasses existing theories of semiotics, ideology, naturalism, realism and credibility. These theories underpin the definitions and discussion on manipulation and credibility. A descriptive survey is used which attempts to discover photojournalists’ views towards credibility. This research draws on qualitative research methods using a largely qualitative questionnaire, which generates both qualitative and quantitative data. The questions are formulated around two case studies of digitally manipulated photographs. The trends and responses in the research data are connected and discussed. The findings of this study are discussed in terms of credibility, awareness of the digital changes, the reason for the changes, the role of a caption, deletion techniques and background changes. The empirical situation is analysed in relation to the theoretical discussions and this study’s theorisation of photographic representation

Finding the Hidden: Detecting Atypical Affective States from Physiological Signals

In cognitive science, intuition is described as a strategy of processing information that relies on people's instinctive and emotional criteria. When compared with the deliberate choices made after conscious reasoning, the quick and intuitive decision making strategies can be more effective. The intuitive thinking provokes changes in human physiological responses which can be measured by sensors. Utilising physiological reactions, previous work shows that atypical patterns such as emotion expressions and image manipulations can be identified. This thesis expands the exploration to examine whether more atypical human behaviour can be recognised from physiological signals. The examined subtly atypical behaviour includes depression, doubt and deception, Depression is a serious chronic mental disease and is considered as an atypical health condition in people. Doubt is defined as a non-deliberate attempt to mislead others and is a passive form of deception, representing an atypicality from honest behaviours. Deception is a more purposeful attempt to deceive, and thus is a distinct type of atypicality than honest communication. Through examining physiological reactions from presenters who have a particular atypical behaviour or condition, and observers who view behaviours of presenters, this research aims to recognise atypicality in human behaviour. A collection of six user studies are conducted. In two user studies, presenters are asked to conduct doubting and deceiving behaviours, while the remaining user studies involve observers watching behaviours of presenters who suffer from depression, have doubt, or have conducted deception. Physiological reactions of both presenters and observers are collected, including Blood Volume Pulse, Electrodermal Activity, Skin Temperature and Pupillary Responses. Observers are also asked to explicitly evaluate whether the viewed presenters were being depressed, doubting, or deceiving. Investigations upon physiological data in this thesis finds that detectable cues corresponding with depression, doubt and deception can be found. Viewing depression provokes visceral physiological reactions in observers that can be measured. Such physiological responses can be used to derive features for machine learning models to accurately distinguish between healthy individuals and people with depression. By contrast, depression does not provoke strong conscious recognition in observers, resulting in a conscious evaluation accuracy slightly above chance level. Similar results are also found in detecting doubt and deception. People with doubt and deceit elicit consistent physiological reactions within themselves. These bodily responses can be utilised by machine learning models or deep learning models to recognise doubt or deception. The doubt and deceit in presenters can also be recognised using physiological signals in observers, with excellent recognition rates which are higher when compared with the conscious judgments from the same group of observers. The results indicate that atypicality in presenters can both be captured by physiological signals of presenters and observers. Presenters' physiological reactions contribute to higher recognition of atypicality, but observers' physiological responses can serve as a comparable alternative. The awareness of atypicality among observers happens physiologically, so can be used by machine learning models, even when they do not reach the consciousness of the person. The research findings lead to a further discussion around the implications of observers' physiological responses. Decision support applications which utilise a quantifiable measure of people's unconscious and intuitive 'gut feeling' can be developed based on the work reported here to assist people with medical diagnosis, information credibility evaluation, and criminal detection. Further research suggests exploring more atypical behaviours in the wild

Image manipulation: Photoshop as a data-measurement tool

Researchers believe that image manipulation threatens photography\u27s perceived objectivity of capturing moments in history. Current research exists that is aimed at determining whether images have been subjected to methods of manipulation. While this research is thorough in its approaches to detection, it lacks methods that would facilitate the measurement of those manipulations; This study uses Photoshop to measure the qualitative changes in images. The aesthetic dimensions set forth by Gillian Rose (2007) such as content, color, spatial organization, and light can be isolated, manipulated, and ultimately measured; This research is aimed at facilitating additional questions regarding what constitutes image manipulation, the extent of image manipulation using the methods described herein, and how image manipulation may affect the viewer. It also hopes to show that widely accepted practices of image modification need to be revisited as technologies continue to update at an unprecedented rate

Eye Tracking to Support eLearning

Online eLearning environments to support student learning are of growing importance. Students are increasingly turning to online resources for education; sometimes in place of face-to-face tuition. Online eLearning extends teaching and learning from the classroom to a wider audience with different needs, backgrounds, and motivations. The one-size-fits-all approach predominately used is not effective for catering to the needs of all students. An area of the increasing diversity is the linguistic background of readers. More students are reading in their non-native language. It has previously been established that first English language (L1) students read differently to second English language (L2) students. One way of analysing this difference is by tracking the eyes of readers, which is an effective way of investigating the reading process. In this thesis we investigate the question of whether eye tracking can be used to make learning via reading more effective in eLearning environments. This question is approached from two directions; first by investigating how eye tracking can be used to adapt to individual student’s understanding and perceptions of text. The second approach is analysing a cohort’s reading behaviour to provide information to the author of the text and any related comprehension questions regarding their suitability and difficulty. To investigate these questions, two user studies were carried out to collect eye gaze data from both L1 and L2 readers. The first user study focussed on how different presentation methods of text and related questions affected not only comprehension performance but also reading behaviour and student perceptions of performance. The data from this study was used to make predictions of reading comprehension that can be used to make eLearning environments adaptive, in addition to providing implicit feedback about the difficulty of text and questions. In the second study we investigate the effects of text readability and conceptual difficulty on eye gaze, prediction of reading comprehension, and perceptions. This study showed that readability affected the eye gaze of L1 readers and conceptual difficulty affected the eye gaze of L2 readers. The prediction accuracy of comprehension was consequently increased for the L1 group by increased difficulty in readability, whereas increased difficulty in conceptual level corresponded to increased accuracy for the L2 group. Analysis of participants’ perceptions of complexity revealed that readability and conceptual difficulty interact making the two variables hard for the reader to disentangle. Further analysis of participants’ eye gaze revealed that both the predefined and perceived text complexity affected eye gaze. We therefore propose using eye gaze measures to provide feedback about the implicit reading difficulty of texts read. The results from both studies indicate that there is enormous potential in using eye tracking to make learning via reading more effective in eLearning environments. We conclude with a discussion of how these findings can be applied to improve reading within eLearning environments. We propose an adaptive eLearning architecture that dynamically presents text to students and provides information to authors to improve the quality of texts and questions

Settler Modernism: Alfred Stieglitz's The Steerage and the Vicissitudes of Whiteness, 1890-1930

Settler Modernism traces how Stieglitz’s iconic photograph, The Steerage (1907) came to be known as the first modernist American photograph and how, at each stage of its trajectory into the modernist canon, it was interpreted through settler colonial narratives that served to naturalize whites’ ongoing presence on occupied territories in the twentieth century. Though studies of settler visual cultures typically concentrate on events surrounding acts of colonization, I demonstrate that American modernist photography was continuous with the nineteenth-century history of photography for which settler colonialism was a structural and discursive force that framed photographic vision. I bring The Steerage into conversation with Stieglitz’s photographs of working-class people, Manhattan, and clouds, as well as with artworks by Cézanne, Anne Brigman, Albert Bierstadt, Thomas Cole, and others. By interrogating how the camera’s capacity to distort perceptions of time and land clinched whites’ amnesia regarding the nation’s founding violence, I show how photographs encouraged settlers to imagine themselves as the ancient inhabitants of the continent. I also thread Indigenous histories, philosophies, and visual cultures throughout the text, undermining settler logic with perspectives that make apparent its impracticability. Through concentrated examination of The Steerage’s history, I shed light on how settler colonialism was not only central to the emergence of American modernism, but also to emergent conceptions of white racial identity that followed the closing of the frontier

Animating Truth

Animating Truth examines the rise of animated documentary in the 21st century, and addresses how non-photorealistic animation is increasingly used to depict and shape reality

Narratives of sexually abused women in reflexive therapy : intra-personal and public versions of self

This thesis examines the therapeutic narratives of sexually abused women. It is based on four in-depth case studies and my experience in counselling hundreds of other women. Two opening chapters outline the methodological and theoretical basis upon which these stories have come to be presented. These accounts unfold through a therapeutic facilitation which has been informed by feminist and narrative therapies, Jungian dream analysis, and a vast array of sexual abuse and related literature. My written translation of these experiences, on the other hand, has been shaped greatly by sociological argument. The foremost of these include feminist standpoint theory, reflexive transformation, and symbolic interaction. The bringing together of these fields serves to create two additional and sometimes conflicting voices - therapist and researcher - which are heard in and around the voices of my clients. The main body of the thesis develops, in storied form, clients' attempts to define and reintegrate themselves following sexual violations in light of a lack of self-authority, fears around voicing their trauma, fragmented memories, disassociation from their own language and symbolism, and a general sense of personal invalidity. In the face of these and other obstacles the therapeutically facilitated accounts bring to the fore unique and creative strategies for integrating these similarly dehumanizing experiences. Each narrative also speaks clearly of the need for a perspective outside of the client which will, in reflecting it back to her, hopefully disarm some of its horror for her and eventually allow it to be integrated by her. In addition, popular therapeutic discourse on sexual abuse has inadvertently served to silence many of my clients by removing them from this experience through a reconstruction of it for them in a theory and language that falls short of capturing its essence. These narrative reconstructions alternatively dispense with those and other descriptions of the client's trauma in favour of internally produced symbols and associations. Just as the sexual abuse narrative needs a discourse into which it can flow in order for it to be heard, it needs also to first be made right at the intra-personal level before it can be widely shared. Within the context of this thesis the therapist has mediated the client's story while the sociologist has sought and amplified its social significance

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field