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In today's social media we see an increase in the use of filters, filters that can distort one's appearance and surroundings, making one wonder what is real and authentic. This essay will analyze two different apps intended for social media that use the popular automated editing tools; Augmented Reality(AR)- and Artificial Intelligence (AI), to find how easily accessible they are and whether the results seem authentic. Through a semiotic approach, I begin the analysis by visually examining the AR and AI filter in the apps to see how they are represented and then what effect it has when applying it on a selected portrait. My findings will contribute to gaining more understanding within the subject of image manipulation and filter, as well as helping me and other graphic designers to increase awareness around consequences when using tools that alter reality.

In today's social media we see an increase in the use of filters, filters that can distort one's appearance and surroundings, making one wonder what is real and authentic. This essay will analyze two different apps intended for social media that use the popular automated editing tools; Augmented Reality(AR)- and Artificial Intelligence (AI), to find how easily accessible they are and whether the results seem authentic. Through a semiotic approach, I begin the analysis by visually examining the AR and AI filter in the apps to see how they are represented and then what effect it has when applying it on a selected portrait. My findings will contribute to gaining more understanding within the subject of image manipulation and filter, as well as helping me and other graphic designers to increase awareness around consequences when using tools that alter reality.

3D-aware generative adversarial networks (GAN) are widely adopted in generating and editing neural radiance fields (NeRF). However, these methods still suffer from GAN-related issues including degraded diversity and training instability. Moreover, 3D-aware GANs consider NeRF pipeline as regularizers and do not directly operate with 3D assets, leading to imperfect 3D consistencies. Besides, the independent changes in disentangled editing cannot be ensured due to the sharing of some shallow hidden features in generators. To address these challenges, we propose the first purely diffusion-based three-stage framework for generative and editing tasks, with a series of well-designed loss functions that can directly handle 3D models. In addition, we present a generalizable neural point field as our 3D representation, which explicitly disentangles geometry and appearance in feature spaces. For 3D data conversion, it simplifies the preparation pipeline of datasets. Assisted by the representation, our diffusion model can separately manipulate the shape and appearance in a hierarchical manner by image/text prompts that are provided by the CLIP encoder. Moreover, it can generate new samples by adding a simple generative head. Experiments show that our approach outperforms the SOTA work in the generative tasks of direct generation of 3D representations and novel image synthesis, and completely disentangles the manipulation of shape and appearance with correct semantic correspondence in the editing tasks. © 2023 Eurographics - The European Association for Computer Graphics and John Wiley & Sons Ltd.

The image as a visual support of the lie, in parallel to its recognized capacity to constitute itself as evidence of the reality, has had a great social repercussion since its inception. This article aims to analyze the phenomenon of “fake news” in photojournalism and, specifically, in photography in the field of the mass media; very especially in the context of news agencies. The objective of the work has two aspects: on the one hand, to establish as an approximation, the tools and resources – taking into account their evolution – that have been used to construct false images from the moment of the invention of photography and, secondly, point out a possible typology of image manipulation according to the characteristics established, a common denominator, of the most prominent situations in the reference studies in the research carried out in this field. Criteria that will be applied to the study of a specific case, that of image manipulation in the Spanish Agency EFE. Work that shows the scarce photographic manipulation (photographic “fake news”) in the studied institution, allows to conclude the existence of quality in the agency’s photojournalistic information and confirms the social repercussion of the subjects of manipulation analyzed., La imagen como soporte visual de la mentira, en paralelo a su reconocida capacidad para constituirse como evidencia de lo real, ha tenido desde sus inicios una gran repercusión social. Este artículo pretende analizar el fenómeno de las “fake news” en el ejercicio del fotoperiodismo y, en concreto, en la fotografía en el ámbito de los medios de comunicación; muy especialmente en el contexto de las agencias de noticias. El objetivo del trabajo tiene dos vertientes: por un lado, establecer como aproximación las herramientas y recursos –teniendo en consideración su evolución- que se han empleado para construir imágenes falsas desde el mismo momento de la invención de la fotografía y, en segundo término, señalar una posible tipología de manipulación de la imagen según las características establecidas, como denominador común, de las situaciones más destacadas por los estudios de referencia en la investigación realizada en este ámbito. Criterios que serán aplicados al estudio de un caso concreto, el de la manipulación de la imagen en la española Agencia EFE. Trabajo que evidencia la escasa manipulación fotográfica (“fake news” fotográficas) en la institución estudiada, permite concluir la existencia de calidad en la información fotoperiodística de agencia y constata la repercusión social de los casos de manipulación analizados.  &nbsp

Image forgery/manipulation is one of the most alarming topics and becomes a major concern about different social media platforms regarding one’s privacy and safety. Therefore, the detection of the manipulated images is of immense interest to the researchers in the recent years. Despite the availability of numerous image forgery detection (IFD) datasets, very few particularly address the actual challenge by collecting the manipulated images from real-world scenario, e.g., collection of images from social media. Consequently, the contextual knowledge behind using the manipulated images remains unachieved. In order to address these issues, we propose an indigenous social media image forgery detection database, naming SMIFD-1000. This dataset provides rich annotations from several aspects: (a) image level: image regions that helps to classify pixel-level information; (b) forgery type: provide rich information about manipulation and (c) target and motif of manipulations: provide contextual rich knowledge about manipulation, which is significantly important from the perspective of social science. Finally, we would examine and benchmark the effectiveness of several publicly available algorithms on this dataset to demonstrate its usefulness. Results show that the dataset is highly challenging and will serve as an important benchmark for the existing and future IFD algorithms., Funding agencies:Information and Communication Technology (ICT) Division, (Ministry of Post, Telecommunication, and Information Technology) Government of the People's Republic of Bangladesh 56.00.0000.028.33.093.19-431Blackbird.AI

A new style transfer-based image manipulation framework combining generative networks and style transfer networks is presented in this paper. Unlike conventional style transfer tasks, we tackle a new task, text-guided image manipulation. We realize style transfer-based image manipulation that does not require any reference style images and generate a style image from the user's input sentence. In our method, since an initial reference input sentence for a content image can automatically be given by an image-to-text model, the user only needs to update the reference sentence. This scheme can help users when they do not have any images representing the desired style. Although this text-guided image manipulation is a new challenging task, quantitative and qualitative comparisons showed the superiority of our method.

This paper studies whether a perceptual visual system can simulate human-like cognitive capabilities by training a computational model to predict the output of an action using language instruction. The aim is to ground action words such that an AI is able to generate an output image that outputs the effect of a certain action on an given object. The output of the model is a synthetic generated image that demonstrates the effect that the action has on the scene. This work combines an image encoder, language encoder, relational network, and image generator to ground action words, and then visualize the effect an action would have on a simulated scene. The focus in this work is to learn meaningful shared image and text representations for relational learning and object manipulation.

Objective. The research to proceed has as objective analyzes the new contents of spread of false information, like this looking for to consider what would be the “deepfake” and the “fakenews” and the consequences of those image manipulations and veiculação of you announce.Method. To develop an exploratory research with bibliographic survey of published materials, such as articles from scientific journals, in which a literature review was carried out in an easy way to clarify and present the subject of deepfakes still little known, and also presented that The way it is created, it manipulates a point of unbridled maneuver in front of social networks.Results. It is known that today the software and applications for smatphones provide, very skillfully, that users manipulate images with extreme ease, the so-called fakeApp, which are tools that allow alteration and manipulation of images in a way that do not leave visual clues of their alteration, and may be indistinguishable from authentic ones. An example of the result of these manipulations is the “deepfake”, is the technique that replaces the face of one person by another in a video, in the current panorama it is common to visualize fake videos, which generate fakenews, or fake news, widely disseminated on social networks and that fit for gaining some credibility due to the difficulty of distinguishing the veracity in the image shown there, as much as the adulteration marks are imperceptible. What facilitates the production of “fakenews” is that any user with limited programming knowledge and little technological learning can create “deepfakes,” and this type of production has triggered challenges for legal professionals, who still find a significant difference between “deepfakes” and authentic videos., Objetivo. A pesquisa a seguir tem como objetivo analisar os novos conteúdos de disseminação de informações falsas, assim buscando conceituar o que seriam as “deepfake” e as “fakenews” e as consequências dessas manipulações de imagem e veiculação de noticias.Metodo. Desenvolveu-se uma pesquisa exploratória com levantamento bibliográfico de materiais previamente publicados, como artigos de periódicos científicos, em que foi realiza uma revisão de literatura apropriada de maneira a esclarecer e apresentar o assunto sobre as “deepfakes” ainda pouco conhecida, além disso, apresentar de que maneira ela é criada, manipulada a ponto de se dissemina de mananeira desenfreada frente às redes sociais.Resultados. Sabe-se que hoje os softwares e aplicativos para smatphones proporcionam, de modo muito hábil, que usuários manipulem imagem com extrema facilidade, os chamados fakeApp,que são ferramentas que permitem alteração e manipulação de imagens de maneira que não deixem pistas visuais de sua alteração, podendo ser indistinguíveis aos autênticos. Exemplo do resultado destas manipulações é a “deepfake”, é a técnica que substitui o rosto de uma pessoa por outra em um vídeo, no panorama atual é comum visualizar vídeos falsos, o que geram as “fakenews”, ou notícias falsas, muito veiculadas nas redes sociais e que cabem por ganhar certa credibilidade devido à dificuldade de distinguir a veracidade na imagem ali mostrada, tão quão são imperceptíveis as marcas de adulteração. O que facilita a produção das “fakenews”, é que qualquer usuário com conhecimento limitado de programação e pouca aprendizagem tecnológica pode criar “deepfakes” e esse tipo de produção tem desencadeado desafios aos profissionais forenses, que ainda encontram significativa diferença entre as “deepfakes” e os vídeos autênticos., Objetivo. La siguiente investigación pretende analizar los nuevos contenidos de difusión de información falsa, buscando así conceptualizar lo que serían las "deepfake" y las "fakenews" y las consecuencias de estas manipulaciones de imagen y difusión de noticias.Metodo. Se desarrolló una investigación exploratoria con un relevamiento bibliográfico de materiales previamente publicados, como artículos de revistas científicas, en la que se realizó una adecuada revisión bibliográfica para aclarar y presentar el tema sobre los "deepfakes", que aún es poco conocido, así como presentar cómo se crea y manipula hasta su difusión rampante a través de las redes sociales.Resultados. Es sabido que hoy en día los programas y aplicaciones para smartphones facilitan, de forma muy hábil, que los usuarios manipulen las imágenes con extrema facilidad, las llamadas fakeApp, que son herramientas que permiten alterar y manipular las imágenes de forma que no dejen pistas visuales de su alteración, y puedan ser indistinguibles de las auténticas. Un ejemplo del resultado de estas manipulaciones es el "deepfake", que es la técnica que sustituye la cara de una persona por otra en un vídeo, en el panorama actual es común ver vídeos falsos, que generan las "fakenews", o noticias falsas, muy difundidas en las redes sociales y que encajan ganando cierta credibilidad debido a la dificultad de distinguir la veracidad en la imagen que allí se muestra, por lo que lo imperceptible son las marcas de manipulación. Lo que facilita la producción de "fakenews", es que cualquier usuario con conocimientos limitados de programación y poco aprendizaje tecnológico puede crear "deepfakes" y este tipo de producción ha desencadenado retos para los profesionales forenses, que siguen encontrando diferencias significativas entre los "deepfakes" y los vídeos auténticos.

This paper studies whether a perceptual visual system can simulate human-like cognitive capabilities by training a computational model to predict the output of an action using language instruction. The aim is to ground action words such that an AI is able to generate an output image that outputs the effect of a certain action on an given object. The output of the model is a synthetic generated image that demonstrates the effect that the action has on the scene. This work combines an image encoder, language encoder, relational network, and image generator to ground action words, and then visualize the effect an action would have on a simulated scene. The focus in this work is to learn meaningful shared image and text representations for relational learning and object manipulation.

This paper studies whether a perceptual visual system can simulate human-like cognitive capabilities by training a computational model to predict the output of an action using language instruction. The aim is to ground action words such that an AI is able to generate an output image that outputs the effect of a certain action on an given object. The output of the model is a synthetic generated image that demonstrates the effect that the action has on the scene. This work combines an image encoder, language encoder, relational network, and image generator to ground action words, and then visualize the effect an action would have on a simulated scene. The focus in this work is to learn meaningful shared image and text representations for relational learning and object manipulation.

This paper studies whether a perceptual visual system can simulate human-like cognitive capabilities by training a computational model to predict the output of an action using language instruction. The aim is to ground action words such that an AI is able to generate an output image that outputs the effect of a certain action on an given object. The output of the model is a synthetic generated image that demonstrates the effect that the action has on the scene. This work combines an image encoder, language encoder, relational network, and image generator to ground action words, and then visualize the effect an action would have on a simulated scene. The focus in this work is to learn meaningful shared image and text representations for relational learning and object manipulation.

This paper studies whether a perceptual visual system can simulate human-like cognitive capabilities by training a computational model to predict the output of an action using language instruction. The aim is to ground action words such that an AI is able to generate an output image that outputs the effect of a certain action on an given object. The output of the model is a synthetic generated image that demonstrates the effect that the action has on the scene. This work combines an image encoder, language encoder, relational network, and image generator to ground action words, and then visualize the effect an action would have on a simulated scene. The focus in this work is to learn meaningful shared image and text representations for relational learning and object manipulation.

Fake or manipulated images propagated through the Web and social media have the capacity to deceive, emotionally distress, and influence public opinions and actions. Yet few studies have examined how individuals evaluate the authenticity of images that accompany online stories. This article details a 6-batch large-scale online experiment using Amazon Mechanical Turk that probes how people evaluate image credibility across online platforms. In each batch, participants were randomly assigned to 1 of 28 news-source mockups featuring a forged image, and they evaluated the credibility of the images based on several features. We found that participants’ Internet skills, photo-editing experience, and social media use were significant predictors of image credibility evaluation, while most social and heuristic cues of online credibility (e.g. source trustworthiness, bandwagon, intermediary trustworthiness) had no significant impact. Viewers’ attitude toward a depicted issue also positively influenced their credibility evaluation.

Fake or manipulated images propagated through the Web and social media have the capacity to deceive, emotionally distress, and influence public opinions and actions. Yet few studies have examined how individuals evaluate the authenticity of images that accompany online stories. This article details a 6-batch large-scale online experiment using Amazon Mechanical Turk that probes how people evaluate image credibility across online platforms. In each batch, participants were randomly assigned to 1 of 28 news-source mockups featuring a forged image, and they evaluated the credibility of the images based on several features. We found that participants’ Internet skills, photo-editing experience, and social media use were significant predictors of image credibility evaluation, while most social and heuristic cues of online credibility (e.g. source trustworthiness, bandwagon, intermediary trustworthiness) had no significant impact. Viewers’ attitude toward a depicted issue also positively influenced their credibility evaluation.

Image forgery or manipulation changes the contents of a set of original images to create a new image. Unfortunately, manipulated images become a growing concern with respect to spreading misinformation via image sharing in the social media. Despite the availability of a large number of automatic Image Forgery Detection (IFD) methods, their evaluation in real-world benchmarks seems to be limited due to the lack of diverse datasets. Moreover, the motifs behind the manipulation remains unclear. This research aims to address these issues by proposing a novel social media IFD database, called SMIFD-500, to evaluate the efficiency and generalizability of the IFD methods. The unique property of this dataset is the availability of the technical and social attributes in its ground truth annotations. These will benefit the scientific community to develop efficient methods by exploiting such annotations. Moreover, it provides interesting statistics, which highlights the motifs of image manipulation from social science perspective.

The growing ease with which digital images can be convincingly manipulated and widely distributed on the Internet makes viewers increasingly susceptible to visual misinformation and deception. In situations where ill-intentioned individuals seek to deliberately mislead and influence viewers through fake online images, the harmful consequences could be substantial. We describe an exploratory study of how individuals react, respond to, and evaluate the authenticity of images that accompany online stories in Internet-enabled communications channels. Our preliminary findings support the assertion that people perform poorly at detecting skillful image manipulation, and that they often fail to question the authenticity of images even when primed regarding image forgery through discussion. We found that viewers make credibility evaluation based mainly on non-image cues rather than the content depicted. Moreover, our study revealed that in cases where context leads to suspicion, viewers apply post-hoc analysis to support their suspicions regarding the authenticity of the image.

The growing ease with which digital images can be convincingly manipulated and widely distributed on the Internet makes viewers increasingly susceptible to visual misinformation and deception. In situations where ill-intentioned individuals seek to deliberately mislead and influence viewers through fake online images, the harmful consequences could be substantial. We describe an exploratory study of how individuals react, respond to, and evaluate the authenticity of images that accompany online stories in Internet-enabled communications channels. Our preliminary findings support the assertion that people perform poorly at detecting skillful image manipulation, and that they often fail to question the authenticity of images even when primed regarding image forgery through discussion. We found that viewers make credibility evaluation based mainly on non-image cues rather than the content depicted. Moreover, our study revealed that in cases where context leads to suspicion, viewers apply post-hoc analysis to support their suspicions regarding the authenticity of the image.

The growing ease with which digital images can be convincingly manipulated and widely distributed on the Internet makes viewers increasingly susceptible to visual misinformation and deception. In situations where ill-intentioned individuals seek to deliberately mislead and influence viewers through fake online images, the harmful consequences could be substantial. We describe an exploratory study of how individuals react, respond to, and evaluate the authenticity of images that accompany online stories in Internet-enabled communications channels. Our preliminary findings support the assertion that people perform poorly at detecting skillful image manipulation, and that they often fail to question the authenticity of images even when primed regarding image forgery through discussion. We found that viewers make credibility evaluation based mainly on non-image cues rather than the content depicted. Moreover, our study revealed that in cases where context leads to suspicion, viewers apply post-hoc analysis to support their suspicions regarding the authenticity of the image.

„Vanishing Voids. Motive des Verschwindens in der zeitgenössischen Kunst“ untersucht konzeptuelle, künstlerische Strategien im Wechselspiel zwischen Sich zeigen und Entziehen. Viele zeitgenössische Künstler_innen versuchen die Grenzen des Darstellbaren auszuloten und thematisieren Absenz, Auslöschung, Leerstellen und sogar das Verschwinden selbst in ihren Werken. Zu Beginn des 21. Jahrhunderts wird das schmale Oeuvre des niederländischen Künstlers Bas Jan Ader wiederentdeckt und etliche junge Künstler_innen rekurrieren, animiert durch die nun mittels YouTube schnell verbreiteten Videos, auf das Werk desjenigen, der buchstäblich verschwunden ist. 1975 bestieg er im Rahmen seines Projekts „In Search of the Miraculous“ ein kleines Seegelboot, um alleine von den USA nach Hause nach Holland zu fahren. Er kam nie an. Ein Künstlermythos ist entstanden. Es wird zudem hinterfragt, warum sich fast 60 Jahre nachdem Yves Klein „Le Vide“, „Die Leere“, in der Galerie Iris Clert in Paris ausstellte, kaum etwas in der Rezeption zeitgenössischer Kunst getan hat, und nach wie vor Absenz und das scheinbare Fehlen künstlerischen Schaffens in der Lage sind, die Gemüter der Rezipient_innen zu erhitzen. Ähnlich wie das Oeuvre Bas Jan Aders wird besonders ein Werk von Yves Klein heute von jungen Künstler_innen häufig appropriiert oder als Quelle herangezogen: „Der Sprung ins Leere“. Am 27.11.1960 gibt der Künstler eine Zeitung, „Dimanche. Le Journal d‘un seul jour“, heraus, deren Titel ein Foto zeigt, auf dem der Künstler mit weit ausgebreiteten Armen aus dem Fenster springt. Im Kapitel „Manipulation, Suspense und ephemere Gesten“ werden Oeuvres von Künstler_innen vorgestellt, die in keinem Zusammenhang mit Ader oder Klein stehen, sich aber intensiv mit den Grenzen der Wahrnehmung, mit (Bild)Manipulation und dem Wechselspiel des Zeigens und Entziehens beschäftigen. Phänomene der An- und Abwesenheit wie zum Beispiel Schatten und Methoden der Manipulation, wie sie in der Fotografie und im Fi, “Vanishing Voids. Motifs of disappearance in contemporary art” investigates conceptual, artistic strategies in the interplay between showing oneself and withdrawing. Many contemporary artists try to explore the boundaries of what can be depicted and thematize absence, extinction, vacancies and even disappearances themselves in their works. At the beginning of the 21st century, the slender oeuvre of the Dutch artist Bas Jan Ader was rediscovered and a lot of young artists referred, animated by the videos, which are now widely distributed via YouTube, to the work of the one who has literally disappeared. In 1975, in the context of his “In Search of the Miraculous” project, he boarded a small sailboat to drive home from the USA to Holland. He never arrived. An artist myth has arisen. It is also questioned why almost 60 years after Yves Klein “Le Vide”, the “Exhibition of the Void”, exhibited in the Iris Clert Gallery in Paris, hardly anything happened concerning the reception of contemporary art and still absence and the apparent lack of artistic producing are able to heat the minds of the recipients. Similar to the oeuvre of Bas Jan Ader especially one work of Yves Klein is frequently appropriated by artists or taken as a source: “Leap into the Void”. On Sunday, November 27th, 1960 the artist edited a newspaper, “Dimanche. Le Journal dun seul jour”, whose title shows a photograph on which the artist jumps out of the window with wide spread arms. In the chapter on “Manipulation, Suspense, and Ephemeral Gestures”, oeuvres are presented by artists who are unrelated to Ader or Klein, but are intensively concerned with the limits of perception, manipulation and the interplay of pointing and withdrawing. Phenomena of presence and absence, such as shadows, and methods of manipulation, such as are used in photography and film, are at the center of the interest of the artists. The chapter “Transcendence, Artistic Myths, Christian Iconography and Paranormal Phenomena” reveals, eingereicht von Mag.a phil. Ingeborg Susanne Erhart, Abweichender Titel laut Übersetzung der Verfasserin/des Verfassers, Universität Innsbruck, Dissertation, 2017, OeBB, (VLID)2211073

Research integrity issues fill the academic news, and include plagiarism, data falsification and image manipulation. Integrity violations are complex because of the gray zones between where bad practice ends and genuine malpractice begin. No real consensus exists about the boundaries, even though many people have strong opinions. The goal of this panel is to engage in a scholarly discussion about integrity issues using specific examples drawn from the book “Quantifying Research Integrity” (Seadle, 2017)., Everything Changes, Everything Stays the Same? Understanding Information Spaces. 15th International Symposium of Information Science (ISI 2017), Berlin, Germany, 13.03.2017 - 15.03.2017

We describe a method for detecting physical inconsistencies in lighting from the shading and shadows in an image. This method imposes a multitude of shading- and shadow-based constraints on the projected location of a distant point light source. The consistency of a collection of such constraints is posed as a linear programming problem. A feasible solution indicates that the combination of shading and shadows is physically consistent, while a failure to find a solution provides evidence of photo tampering.

We describe a method for detecting physical inconsistencies in lighting from the shading and shadows in an image. This method imposes a multitude of shading- and shadow-based constraints on the projected location of a distant point light source. The consistency of a collection of such constraints is posed as a linear programming problem. A feasible solution indicates that the combination of shading and shadows is physically consistent, while a failure to find a solution provides evidence of photo tampering.

We describe a geometric technique to detect physically inconsistent arrangements of shadows in an image. This technique combines multiple constraints from cast and attached shadows to constrain the projected location of a point light source. The consistency of the shadows is posed as a linear programming problem. A feasible solution indicates that the collection of shadows is physically plausible, while a failure to find a solution provides evidence of photo tampering. © 2013 ACM.

We describe a geometric technique to detect physically inconsistent arrangements of shadows in an image. This technique combines multiple constraints from cast and attached shadows to constrain the projected location of a point light source. The consistency of the shadows is posed as a linear programming problem. A feasible solution indicates that the collection of shadows is physically plausible, while a failure to find a solution provides evidence of photo tampering. © 2013 ACM.

The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. In this article we describe a new forensic technique that focuses on geometric inconsistencies that arise when fake reflections are inserted into a photograph or when a photograph containing reflections is manipulated. This analysis employs basic rules of reflective geometry and linear perspective projection, makes minimal assumptions about the scene geometry, and only requires the user to identify corresponding points on an object and its reflection. The analysis is also insensitive to common image editing operations such as resampling, color manipulations, and lossy compression. We demonstrate this technique with both visually plausible forgeries of our own creation and commercially produced forgeries. © 2012 ACM.

The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. In this article we describe a new forensic technique that focuses on geometric inconsistencies that arise when fake reflections are inserted into a photograph or when a photograph containing reflections is manipulated. This analysis employs basic rules of reflective geometry and linear perspective projection, makes minimal assumptions about the scene geometry, and only requires the user to identify corresponding points on an object and its reflection. The analysis is also insensitive to common image editing operations such as resampling, color manipulations, and lossy compression. We demonstrate this technique with both visually plausible forgeries of our own creation and commercially produced forgeries. © 2012 ACM.

Background: Computed tomography (CT) is becoming increasingly popular as a non-invasive method for visualizing the coronary arteries but patient radiation doses are still an issue. Postprocessing filters such as 2D adaptive non-linear filters might help to reduce the dose without loss of image quality. less thanbrgreater than less thanbrgreater thanPurpose: To investigate whether the use of a 2D, non-linear adaptive noise reduction filter can improve image quality in cardiac computed tomography angiography (CCTA). less thanbrgreater than less thanbrgreater thanMaterial and Methods: CCTA examinations were performed in 36 clinical patients on a dual source CT using two patient dose levels: maximum dose during diastole and reduced dose (20% of maximum dose) during systole. One full-dose and one reduced-dose image were selected from each of the examinations. The reduced-dose image was duplicated and one copy postprocessed using a 2D non-linear adaptive noise reduction filter, resulting in three images per patient. Image quality was assessed using visual grading with three criteria from the European guidelines for assessment of image quality and two additional criteria regarding the left main artery and the overall image quality. Also, the HU value and its standard deviation were measured in the ascending and descending aorta. Data were analyzed using Visual Grading Regression and paired t-test. less thanbrgreater than less thanbrgreater thanResult: For all five criteria, there was a significant (P andlt; 0.01 or better) improvement in perceived image quality when comparing postprocessed low-dose images with low-dose images without noise reduction. Comparing full dose images with postprocessed low-dose images resulted in a considerably larger, significant (P andlt; 0.001) difference. Also, there was a significant reduction of the standard deviation of the HU values in the ascending and descending aorta when comparing postprocessed low-dose images with low-dose images wit

The SRI Cartographic Modeling Environment has been created to support research on interactive, semiautomated, and automated computer-based cartographic activities. The underlying image manipulation capabilities are provided by the SRI ImagCalc(TM) system. The cartographic features and data that can be entered include multiple images, camera models, digital terrain elevation data, point, line, and area cartographic features, and a wide assortment of three-dimensional objects. Interactive capabilities include free-hand feature lighting entry, altering features while constraining them to conform to the terrain and lighting geometry, adjustment of feature parameters, and the adjustment of the camera model to display the scene features from arbitrary viewpoints. Cartographic features are depictable either as wire-frame sketches for interactive purposes or as texture-mapped renderings for realistic scene synthesis. High-quality simulated scenes are created by texture-mapping images onto terrain data and adding renderings of cartographic features using depth-buffering and antialiasing techniques. Motion sequences can be created by choosing a series of camera models and rendering the simulated appearance of the scene from each viewpoint., Presented at the Image Understanding Workshop, held on Cambridge, MA on 6-8 April 1998. Pub. in the Proceedings of the Image Understanding Workshop, 1988.

This paper presents a new class of interactive image editing operations designed to maintain physical consistency between multiple images of a physical 3D object. The distinguishing feature of these operations is that edits to any one image propagate automatically to all other images as if the (unknown) 3D object had itself been modified. The approach is useful first as a power-assist that enables a user to quickly modify many images by editing just a few, and second as a means for constructing and editing image-based scene representations by manipulating a set of photographs. The approach works by extending operations like image painting, scissoring, and morphing so that they alter an object's plenoptic function in a physically-consistent way, thereby affecting object appearance from all viewpoints simultaneously. A key element in realizing these operations is a new volumetric decomposition technique for reconstructing an object's plenoptic function from an incomplete set of camera viewpoints.

This paper presents a new class of interactive image editing operations designed to maintain physical consistency between multiple images of a physical 3D object. The distinguishing feature of these operations is that edits to any one image propagate automatically to all other images as if the (unknown) 3D object had itself been modified. The approach is useful first as a power-assist that enables a user to quickly modify many images by editing just a few, and second as a means for constructing and editing image-based scene representations by manipulating a set of photographs. The approach works by extending operations like image painting, scissoring, and morphing so that they alter an object's plenoptic function in a physically-consistent way, thereby affecting object appearance from all viewpoints simultaneously. A key element in realizing these operations is a new volumetric decomposition technique for reconstructing an object's plenoptic function from an incomplete set of camera viewpoints.

Tato práce se zabývá tvorbou webového nástroje pro anotaci obrazových dat. Teoretická část specifikuje aplikaci, její design a funkcionalitu. Praktická část se zabývá implementací webového nástroje pro anotaci obrazových dat jako bod, přímka, obdelník, polygon se zaměřením na modularitu a lehkou rozšířitelnost nástroje pro ruzné typy anotací a dále implementací funkcí pro manipulaci s obrazem a jeho transformaci. Pro praktickou část této práce byla použita knihovna Flask s využitím jazyků Python, HTML, Javascript. Nástroj byl vytvářen a vyvíjen iterativně., This work deals with the creation of web tool for image data annotation. The theoretical part specifies the application, its design and functionality. The practical part deals with the implementation of the web tool for image data annotation such as point, line, rectangle, polygon with focus on modularity and easy extensibility of the tool for various types of annotations and implementation of image manipulation and transformation functions. For practical part of this work was used library Flask using Python, HTML, Javascript. The tool was created and developed iteratively.

Tato práce se zabývá tvorbou webového nástroje pro anotaci obrazových dat. Teoretická část specifikuje aplikaci, její design a funkcionalitu. Praktická část se zabývá implementací webového nástroje pro anotaci obrazových dat jako bod, přímka, obdelník, polygon se zaměřením na modularitu a lehkou rozšířitelnost nástroje pro ruzné typy anotací a dále implementací funkcí pro manipulaci s obrazem a jeho transformaci. Pro praktickou část této práce byla použita knihovna Flask s využitím jazyků Python, HTML, Javascript. Nástroj byl vytvářen a vyvíjen iterativně., This work deals with the creation of web tool for image data annotation. The theoretical part specifies the application, its design and functionality. The practical part deals with the implementation of the web tool for image data annotation such as point, line, rectangle, polygon with focus on modularity and easy extensibility of the tool for various types of annotations and implementation of image manipulation and transformation functions. For practical part of this work was used library Flask using Python, HTML, Javascript. The tool was created and developed iteratively.

Tato práce se zabývá tvorbou webového nástroje pro anotaci obrazových dat. Teoretická část specifikuje aplikaci, její design a funkcionalitu. Praktická část se zabývá implementací webového nástroje pro anotaci obrazových dat jako bod, přímka, obdelník, polygon se zaměřením na modularitu a lehkou rozšířitelnost nástroje pro ruzné typy anotací a dále implementací funkcí pro manipulaci s obrazem a jeho transformaci. Pro praktickou část této práce byla použita knihovna Flask s využitím jazyků Python, HTML, Javascript. Nástroj byl vytvářen a vyvíjen iterativně., This work deals with the creation of web tool for image data annotation. The theoretical part specifies the application, its design and functionality. The practical part deals with the implementation of the web tool for image data annotation such as point, line, rectangle, polygon with focus on modularity and easy extensibility of the tool for various types of annotations and implementation of image manipulation and transformation functions. For practical part of this work was used library Flask using Python, HTML, Javascript. The tool was created and developed iteratively.