Recoding Color Transfer as A Color Homography

Color transfer is an image editing process that adjusts the colors of a picture to match a target picture's color theme. A natural color transfer not only matches the color styles but also prevents after-transfer artifacts due to image compression, noise, and gradient smoothness change. The recently discovered color homography theorem proves that colors across a change in photometric viewing condition are related by a homography. In this paper, we propose a color-homography-based color transfer decomposition which encodes color transfer as a combination of chromaticity shift and shading adjustment. A powerful form of shading adjustment is shown to be a global shading curve by which the same shading homography can be applied elsewhere. Our experiments show that the proposed color transfer decomposition provides a very close approximation to many popular color transfer methods. The advantage of our approach is that the learned color transfer can be applied to many other images (e.g. other frames in a video), instead of a frame-to-frame basis. We demonstrate two applications for color transfer enhancement and video color grading re-application. This simple model of color transfer is also important for future color transfer algorithm design

Root-Polynomial Color Homography Color Correction

Homographies are at the heart of computer vision and they are used in geometric camera calibration, image registration, and stereo vision and other tasks. In geometric computer vision, two images of the same 3D plane captured in two different viewing locations are related by a planar (2D) homography. Recent work showed that the concept of a planar homography mapping can be applied to shading-invariant color correction. In this paper, we extend the color homography color correction idea by incorporating higher order root-polynomial terms into the color correction problem formulation. Our experiments show that our new shading-invariant color correction method can obtain yet more accurate and stable performance compared with the previous 2D color homography method

3D color homography model for photo-realistic color transfer re-coding

Color transfer is an image editing process that naturally transfers the color theme of a source image to a target image. In this paper, we propose a 3D color homography model which approximates photo-realistic color transfer algorithm as a combination of a 3D perspective transform and a mean intensity mapping. A key advantage of our approach is that the re-coded color transfer algorithm is simple and accurate. Our evaluation demonstrates that our 3D color homography model delivers leading color transfer re-coding performance. In addition, we also show that our 3D color homography model can be applied to color transfer artifact fixing, complex color transfer acceleration, and color-robust image stitching

Color Homography: theory and applications

Images of co-planar points in 3-dimensional space taken from different camera positions are a homography apart. Homographies are at the heart of geometric methods in computer vision and are used in geometric camera calibration, 3D reconstruction, stereo vision and image mosaicking among other tasks. In this paper we show the surprising result that homographies are the apposite tool for relating image colors of the same scene when the capture conditions -- illumination color, shading and device -- change. Three applications of color homographies are investigated. First, we show that color calibration is correctly formulated as a homography problem. Second, we compare the chromaticity distributions of an image of colorful objects to a database of object chromaticity distributions using homography matching. In the color transfer problem, the colors in one image are mapped so that the resulting image color style matches that of a target image. We show that natural image color transfer can be re-interpreted as a color homography mapping. Experiments demonstrate that solving the color homography problem leads to more accurate calibration, improved color-based object recognition, and we present a new direction for developing natural color transfer algorithms

An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping

High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV

Метод цветовой консистентности для камер с неизвестной моделью

Современные методы вычислительной фотографии позволяют приблизить качество изображений, получаемых мобильными камерами, к качеству профессиональных фотокамер. Одна из важнейших задач в этой связи – задача обеспечения консистентности цветов различных камер. В настоящей работе предлагается простой и эффективный способ привести цвета одной камеры к другой, основанный на аппроксимации необходимого преобразования сплайном тоновой коррекции и матрицей цветового преобразования. Экспериментальное исследование проведено в достаточно сложном случае, в котором требуется привести в соответствие цвета изображений, полученных с двух принципиально разных сенсоров, а также с использованием дифракционной оптики. Результаты экспериментов показали, что предложенный метод позволяет получить более высокую точность приведения цветов между камерами, чем существующие аналоги.Работа выполнена при поддержке гранта РНФ 22-19-00364

Synchronized Illumination Modulation for Digital Video Compositing

Informationsaustausch ist eines der Grundbedürfnisse der Menschen. Während früher dazu Wandmalereien,Handschrift, Buchdruck und Malerei eingesetzt wurden, begann man später, Bildfolgen zu erstellen, die als sogenanntes ”Daumenkino” den Eindruck einer Animation vermitteln. Diese wurden schnell durch den Einsatz rotierender Bildscheiben, auf denen mit Hilfe von Schlitzblenden, Spiegeln oder Optiken eine Animation sichtbar wurde, automatisiert – mit sogenannten Phenakistiskopen,Zoetropen oder Praxinoskopen. Mit der Erfindung der Fotografie begannen in der zweiten Hälfte des 19. Jahrhunderts die ersten Wissenschaftler wie Eadweard Muybridge, Etienne-Jules Marey und Ottomar Anschütz, Serienbildaufnahmen zu erstellen und diese dann in schneller Abfolge, als Film, abzuspielen. Mit dem Beginn der Filmproduktion wurden auch die ersten Versuche unternommen, mit Hilfe dieser neuen Technik spezielle visuelle Effekte zu generieren, um damit die Immersion der Bewegtbildproduktionen weiter zu erhöhen. Während diese Effekte in der analogen Phase der Filmproduktion bis in die achtziger Jahre des 20.Jahrhunderts recht beschränkt und sehr aufwendig mit einem enormen manuellen Arbeitsaufwand erzeugt werden mussten, gewannen sie mit der sich rapide beschleunigenden Entwicklung der Halbleitertechnologie und der daraus resultierenden vereinfachten digitalen Bearbeitung immer mehr an Bedeutung. Die enormen Möglichkeiten, die mit der verlustlosen Nachbearbeitung in Kombination mit fotorealistischen, dreidimensionalen Renderings entstanden, führten dazu, dass nahezu alle heute produzierten Filme eine Vielfalt an digitalen Videokompositionseffekten beinhalten. ...Besides home entertainment and business presentations, video projectors are powerful tools for modulating images spatially as well as temporally. The re-evolving need for stereoscopic displays increases the demand for low-latency projectors and recent advances in LED technology also offer high modulation frequencies. Combining such high-frequency illumination modules with synchronized, fast cameras, makes it possible to develop specialized high-speed illumination systems for visual effects production. In this thesis we present different systems for using spatially as well as temporally modulated illumination in combination with a synchronized camera to simplify the requirements of standard digital video composition techniques for film and television productions and to offer new possibilities for visual effects generation. After an overview of the basic terminology and a summary of related methods, we discuss and give examples of how modulated light can be applied to a scene recording context to enable a variety of effects which cannot be realized using standard methods, such as virtual studio technology or chroma keying. We propose using high-frequency, synchronized illumination which, in addition to providing illumination, is modulated in terms of intensity and wavelength to encode technical information for visual effects generation. This is carried out in such a way that the technical components do not influence the final composite and are also not visible to observers on the film set. Using this approach we present a real-time flash keying system for the generation of perspectively correct augmented composites by projecting imperceptible markers for optical camera tracking. Furthermore, we present a system which enables the generation of various digital video compositing effects outside of completely controlled studio environments, such as virtual studios. A third temporal keying system is presented that aims to overcome the constraints of traditional chroma keying in terms of color spill and color dependency. ..

Orthographic Learning via Self-Teaching: Evidence from Mandarin Chinese

Diese Dissertation beschäftigt sich mit Fragen des orthographischen Lernprozesses einer nicht-alphabetischen, chinesischen Schrift durch Self-Teaching. Orthographisches Lernen ist definiert als der Prozess, durch den Kinder im Gedächtnis Repräsentationen von Wortformen anlegen. So werden automatisierte Worterkennung und damit flüssiges Lesen möglich. Die Self-Teaching-Hypothese besagt, dass sich die automatisierte Worterkennung durch einen Mechanismus selbstständigen Lernens entwickelt, der Kinder befähigt, die Orthographie neuer Wörter Item für Item zu erlernen. Für diesen Mechanismus ist die phonologische Rekodierung wichtig. Auch die chinesische Orthographie kann aufgrund der internen Struktur der Schriftzeichen und aufgrund der sublexikalischen Phonologie und Semantik durch Self-Teaching erworben werden. Mindestens vier Fünftel aller chinesischen Schriftzeichen sind Phonogramme. Die phonetischen und semantischen Radikale, die in die chinesischen Phonograme eingebettet sind, wurden für vier Experimente nach dem Self-Teaching-Paradigma (Share, 1999) genutzt. An den ersten zwei Experimenten nahmen Drittklässler teil, die anderen beiden waren auf Zweitklässler abgestimmt. Alle Teilnehmer wurden gebeten, selbstständig Kurztexte vorzulesen. Die innere Struktur des Target-Pseudo-Schriftzeichens und die Häufigkeit seiner Darbietung wurden innerhalb der Kurztexte manipuliert. Sowohl unmittelbar nach der Lesephase als auch nach einem dreitägigen Intervall wurden zwei Tests durchgeführt, eine orthographische Entscheidungsaufgabe und eine orthographische Produktionsaufgabe, um den Erfolg des orthographischen Lernens zu erfassen. Das vorrangige Ziel der Experimente war es zu untersuchen, inwiefern orthographisches Lernen im Sinne der Self-Teaching-Hypothese in der visuell komplexen, nicht-alphabetischen chinesischen Schrift möglich ist. Darüber hinaus wurde untersucht, ob Radikale eine Rolle in diesem Lernprozess spielen. Experiment 1 untersuchte den Einfluss von Zhuyin auf den orthographischen Lernprozess im Chinesischen. Zhuyin sind spezielle Zeichen in taiwanesischen Kinderbüchern, die Informationen über die Aussprache unbekannter Schriftzeichen geben. Zhuyin ist vollständig phonologisch transparent und dem Alphabet ähnlich. Basierend auf der Self-Teaching-Hypothese würden externe phonologische Hilfsmittel, in diesem Fall Zhuyin, die Aufmerksamkeit der Kinder von den orthographischen Details ablenken. Diese Vorhersage wurde durch die Ergebnisse von Experiment 1 bestätigt: In den Bedingungen ohne Zhuyin zeigten sich in beiden Tests deutlich stärkere Lerneffekte als in den Bedingungen mit Zhuyin. Im Anschluss an die Beobachtung, dass Zhuyin orthographisches Lernen im Chinesischen beeinträchtigt, befasste sich Experiment 2 mit der Frage, ob phonetische Radikale ausreichend für funktionales Lernen der chinesischen Orthographien sind. Gemäß der Self-Teaching-Hypothese ist davon auszugehen, dass die phonologische Rekodierung kritisch für das orthographischen Lernen ist. Trotzdem (und entgegen der Annahme) unterstützte Zhuyin, also die Angabe der genauen Aussprache, den Prozess des orthographischen Lernens im Chinesischen nicht. Eine mögliche Erklärung dafür ist, dass die Information zur phonetischen Rekodierung, die in das Target-Pseudo-Schriftzeichen selbst eingebettet sind, entscheidend dazu beitragen, Chinesisch lesen zu lernen. In Experiment 2 wurde die Verfügbarkeit der eingebetteten phonetischen Radikale in den Targets manipuliert. In beiden Tests zeigte sich ein robusterer Lerneffekt für Targets mit gegenüber Targets ohne phonetisches Radikal. Ähnlich der morpho-semantischen Information im Englischen kann das semantische Radikal in chinesischen Schriftzeichen eine weitere nützliche Ressource im Erwerb der Lesefähigkeit im Chinesischen sein. Experiment 3 untersuchte den Cueing-Effekt semantischer Radikale, indem entweder solche semantischen Radikale in die Target-Pseudo-Schriftzeichen eingebettet wurden, die einen Hinweis (Cue) auf die Bedeutung geben, oder solche, die keinen Hinweis liefern. Die Teilnehmer zeigten signifikant bessere Leistungen, wenn das semantische Radikal auf die Bedeutung des Targets verwies, als wenn es keinen Hinweis bot. Das Ergebnis weist darauf hin, dass semantische Radikale in ihrer Funktion, auf die Bedeutung der Schriftzeichen hinzuweisen, ebenfalls einen Beitrag zum Erwerb der chinesischen Orthographie leisten. Es ist bekannt, dass die semantische Transparenz den Worterkennungsprozess im Chinesischen beeinflusst. Es ist zu vermuten, dass sie auch das orthographische Lernen beeinflusst. Semantische Transparenz wird als Grad der Übereinstimmung der Bedeutung des semantischen Radikals mit der Bedeutung des gesamten Schriftzeichens definiert. Letztere soll in den Experimenten dieser Studie aus dem Kontext erschlossen werden. Folglich manipulierte Studie 4 die Übereinstimmung zwischen der Target-Bedeutung, die der Kontext nahelegte und der Bedeutung, auf die das semantische Radikal schließen ließ. Es zeigte sich ein genereller, wenn auch nicht-signifikanter Trend in Richtung besserer Lernleistungen für die Bedingungen mit intransparenten semantischen Radikalen. Dies könnte damit zusammenhängen, dass Zweitklässler im Unterschied zu Erwachsenen den semantischen Aspekt auf globaler Ebene noch nicht vollständig nutzen können. Zusammenfassend unterstützt die Dissertation die These, dass die chinesische Orthographie in einem Prozess des Self-Teaching erworben wird. Im Einklang mit der Self-Teaching-Hypothese äußerte sich orthographisches Lernen darin, dass Target-Schriftzeichen häufiger korrekt ausgewählt und häufiger korrekt geschrieben wurden. Ganz allgemein bedeutet das, dass die Self-Teaching-Hypothese auch dann gilt, wenn es um den Erwerb der Lesefähigkeit in einer nicht-alphabetischen Schrift geht. Taiwanesische Kinder lernen die traditionellen chinesischen Schriftzeichen, die visuell komplexer sind als das vereinfachte Skript, das in China benutzt wird. Dabei profitieren sie auch von den phonetischen und semantischen Informationen, die in die Schriftzeichen eingebettet sind, wenn sie sich selbst die orthographischen Details beibringen. Der selbstlernende Aspekt im orthographischen Lernprozess ist wohl universell in unterschiedlichen Schriftsystemen zu finden, und Phonologie spielt auch im Chinesischen für den Erwerb der Lesefähigkeit eine zentrale Rolle.This dissertation investigates the orthographic learning process of a non-alphabetic Chinese script via self-teaching. Orthographic learning is the process by which children commit word forms to memory. Successful orthographic learning leads to automaticity with word recognition; in turn, automated, efficient word recognition facilitates fluent reading. The self-teaching hypothesis proposes that reading fluency is built up via a self-teaching mechanism that empowers orthographic learning of new words on an item-by-item basis. Central to the self-teaching mechanism is phonological recoding. The internal structure properties of Chinese characters and the sublexical phonology and semantics also permit developing readers to self-teach Chinese orthographic forms. More than 80% of the Chinese characters are phonograms. Taking advantage of the phonetic and semantic radicals embedded in Chinese phonograms, four studies were carried out following Share’s (1999) self-teaching paradigm. The first two targeted young readers in Grade 3, whereas the other two studies focused on children in Grade 2. Participants were asked to independently read aloud short texts where the internal structure of target pseudocharacters and the number of exposure were manipulated. Two posttests, including an orthographic choice task and a spelling task, were administered both immediately after the reading phase and after a 3-day interval to measure orthographic learning. The overriding aim of all studies was to explore the possibility of orthographic learning via self-teaching in the visually complex, traditional Chinese script used in Taiwan and Hong Kong, as distinct from the simplified Chinese script used in China. Other aims were to look into issues as to whether radicals play a role in Chinese orthographic learning. Study 1 examined the effect of Zhuyin on Chinese orthographic learning. Zhuyin is the phonological aid system used to list pronunciations alongside unknown characters in Taiwanese child books; Zhuyin is completely transparent and alphabet-like. Based on the self-teaching hypothesis, extraneous phonological aids, such as Zhuyin, would divert children’s attention away from orthographic details. Favoring this prediction, the results on both posttest measures depicted a significantly stronger learning effect in conditions without Zhuyin than those with Zhuyin. Following up on the finding that Zhuyin did not give rise to optimal orthographic learning in Chinese, Study 2 looked at the issue whether phonetic radicals are sufficient for functional learning of Chinese orthographies. One of the fundamental tenets in the self-teaching theory is that phonological recoding is critical to orthographic learning. Zhuyin does not aid the process of Chinese orthographic learning by offering accurate pronunciations as much as previously assumed; it is thus arguable that the phonological recoding opportunities afforded by the phonetic radicals embedded in target pseudocharacters are crucial in learning to read Chinese. Through the manipulation of the availability of phonetic radicals embedded in targets, Study 2 reported a more robust learning effect on both posttest measures when targets were embedded with a phonetic radical than without. Similar to morpho-semantic information in English, the semantic hint embedded in Chinese characters might be another useful resource that unskilled readers can bring to bear upon Chinese orthographic learning. Study 3 tested the cueing effect of semantic radicals by embedding targets with cueing and non-cueing semantic radicals. Children performed significantly better in conditions with cueing semantic radicals than non-cueing ones; this demonstrated that the semantic radicals embedded in characters also modulated Chinese orthographic learning to a certain extent. Semantic transparency has been documented to influence Chinese word recognition; it is possible that semantic transparency also has an impact on orthographic learning. With the working definition that semantic transparency in orthographic learning refers to the semantic relatedness of an embedded semantic radical in relation to the semantic information that is to be instantiated into the target from the context, Study 4 manipulated thus the semantic relatedness between the level of embedded semantic radical and that of the context semantics. The results from Study 4, though not statistically significant, exhibited a general trend towards better learning in semantic opaque conditions. The finding might arise from the fact that, unlike established readers, 2nd grade children have yet to fully appreciate the semantic aspect at a global level. Taken together, the dissertation provided support to Chinese orthographic learning via self-teaching. Consistent with the self-teaching hypothesis, orthographic learning was evidenced with significantly more targets selected and more target spelling patterns reproduced than other alternatives. In general, the self-teaching hypothesis is also valid to account for learning to read in a non-alphabetic script, like Chinese. Taiwanese children learning to read a visually more complex, traditional Chinese script exploited the phonetic and semantic information that is embedded in the writing system to self-teach orthographic details. The self-teaching aspect of orthographic learning is hence universal across disparate writing systems, and phonology is also the key to learning to read Chinese

Context-Enabled Visualization Strategies for Automation Enabled Human-in-the-loop Inspection Systems to Enhance the Situation Awareness of Windstorm Risk Engineers

Insurance loss prevention survey, specifically windstorm risk inspection survey is the process of investigating potential damages associated with a building or structure in the event of an extreme weather condition such as a hurricane or tornado. Traditionally, the risk inspection process is highly subjective and depends on the skills of the engineer performing it. This dissertation investigates the sensemaking process of risk engineers while performing risk inspection with special focus on various factors influencing it. This research then investigates how context-based visualizations strategies enhance the situation awareness and performance of windstorm risk engineers. An initial study investigated the sensemaking process and situation awareness requirements of the windstorm risk engineers. The data frame theory of sensemaking was used as the framework to carry out this study. Ten windstorm risk engineers were interviewed, and the data collected were analyzed following an inductive thematic approach. The themes emerged from the data explained the sensemaking process of risk engineers, the process of making sense of contradicting information, importance of their experience level, internal and external biases influencing the inspection process, difficulty developing mental models, and potential technology interventions. More recently human in the loop systems such as drones have been used to improve the efficiency of windstorm risk inspection. This study provides recommendations to guide the design of such systems to support the sensemaking process and situation awareness of windstorm visual risk inspection. The second study investigated the effect of context-based visualization strategies to enhance the situation awareness of the windstorm risk engineers. More specifically, the study investigated how different types of information contribute towards the three levels of situation awareness. Following a between subjects study design 65 civil/construction engineering students completed this study. A checklist based and predictive display based decision aids were tested and found to be effective in supporting the situation awareness requirements as well as performance of windstorm risk engineers. However, the predictive display only helped with certain tasks like understanding the interaction among different components on the rooftop. For remaining tasks, checklist alone was sufficient. Moreover, the decision aids did not place any additional cognitive demand on the participants. This study helped us understand the advantages and disadvantages of the decision aids tested. The final study evaluated the transfer of training effect of the checklist and predictive display based decision aids. After one week of the previous study, participants completed a follow-up study without any decision aids. The performance and situation awareness of participants in the checklist and predictive display group did not change significantly from first trial to second trial. However, the performance and situation awareness of participants in the control condition improved significantly in the second trial. They attributed this to their exposure to SAGAT questionnaire in the first study. They knew what issues to look for and what tasks need to be completed in the simulation. The confounding effect of SAGAT questionnaires needs to be studied in future research efforts

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings