Drawing Style Research Articles

Perancangan Desain Karakter pada Buku Interaktif Pengenalan Literasi Keuangan untuk Anak Usia Dini

The focus of this design is the creation of character designs on interactive financial literacy books media for early childhood. The method used in this design is qualitative and uses qualitative descriptive analysis techniques. Primary data were obtained from interviews, Focus Group Discussions, and observations, while secondary data were obtained from literature and mass media. The design process begins with collecting references, determining concepts, making design alternatives, final designs, and evaluating designs. Verbal and visual concepts refer to the characteristics of the target audience, namely children aged 4-6 years in Indonesia. The drawing style and illustration refers to the book "Sayur Juara" which is used as a study comparator. Characters that have been selected and evaluated, then applied to interactive book media, stickers, and keychains. Introducing financial literacy is important from early childhood. This research is expected to contribute to improving early childhood financial literacy through the development of character designs in interactive books that are interesting and educational.

Drawing as a window to emotion with insights from tech-transformed participant images

This study delves into expressing primary emotions anger, happiness, sadness, and fear through drawings. Moving beyond the well-researched color-emotion link, it explores under-examined aspects like spatial concepts and drawing styles. Employing Python and OpenCV for objective analysis, we make a breakthrough by converting subjective perceptions into measurable data through 728 digital images from 182 university students. For the prominent color chosen for each emotion, the majority of participants chose red for anger (73.11%), yellow for happiness (17.8%), blue for sadness (51.1%), and black for fear (40.7%). Happiness led with the highest saturation (68.52%) and brightness (75.44%) percentages, while fear recorded the lowest in both categories (47.33% saturation, 48.78% brightness). Fear, however, topped in color fill percentage (35.49%), with happiness at the lowest (25.14%). Tangible imagery prevailed (71.43–83.52%), with abstract styles peaking in fear representations (28.57%). Facial expressions were a common element (41.76–49.45%). The study achieved an 81.3% predictive accuracy for anger, higher than the 71.3% overall average. Future research can build on these results by improving technological methods to quantify more aspects of drawing content. Investigating a more comprehensive array of emotions and examining factors influencing emotional drawing styles will further our understanding of visual-emotional communication.

ТРЕНУВАННЯ НЕЙРОМЕРЕЖІ ДЛЯ СТИЛІЗАЦІЇ ЗОБРАЖЕНЬ

Improving the visualization of projects and portfolios of designers and architects can be achieved by enhancing the illustrativeness and stylization of images using artificial intelligence. The use of neural networks for content generation significantly speeds up the work of designers. Among all the neural networks for image generation, MidJourney shows the best results. After analyzing the licenses and subscription costs of services as well as the models they employ, the Stable Diffusion deep learning neural network was chosen. The Stable Diffusion neural network is open-source, unlike DALL-E and Midjourney, allowing for unlimited content generation. The stylized images were generated in Stable Diffusion using Dreambooth based on the Google Collab platform. The creation of a custom model was conducted in two stages. The first stage involved preparing images for training the Stable Diffusion neural network. The second stage was the direct training of the neural network based on the Google Collab platform. Kobzar's graphic drawings served as the training dataset. Initially, 77 drawings with the same theme were selected for model training. 30 of these were used to train the model after corrections in Adobe Photoshop and Topaz Photo AI. Adjustments included cropping, background removal, printing raster, noise reduction, sharpening, and scaling images. The originality of the work lies in the fact that the trained model was used to create stylized creative images, utilizing excerpts from the poet's poems describing nature and events in a very realistic way. The generated images have successfully passed the Turing test, indicating a realistic reproduction of the style of Taras Shevchenko's drawings and the utilization of the author's poetic text as a prompt. The use of neural networks for generating and styling images as virtual assistants for designers and architects speeds up the creative process and enables the creation of works of any complexity.

Data-driven identification of distinct pain drawing patterns and their association with clinical and psychological factors: a study of 21,123 patients with spinal pain.

The variability in pain drawing styles and analysis methods has raised concerns about the reliability of pain drawings as a screening tool for nonpain symptoms. In this study, a data-driven approach to pain drawing analysis has been used to enhance the reliability. The aim was to identify distinct clusters of pain patterns by using latent class analysis (LCA) on 46 predefined anatomical areas of a freehand digital pain drawing. Clusters were described in the clinical domains of activity limitation, pain intensity, and psychological factors. A total of 21,123 individuals were included from 2 subgroups by primary pain complaint (low back pain (LBP) [n = 15,465]) or midback/neck pain (MBPNP) [n = 5658]). Five clusters were identified for the LBP subgroup: LBP and radiating pain (19.9%), radiating pain (25.8%), local LBP (24.8%), LBP and whole leg pain (18.7%), and widespread pain (10.8%). Four clusters were identified for the MBPNP subgroup: MBPNP bilateral posterior (19.9%), MBPNP unilateral posterior + anterior (23.6%), MBPNP unilateral posterior (45.4%), and widespread pain (11.1%). The clusters derived by LCA corresponded to common, specific, and recognizable clinical presentations. Statistically significant differences were found between these clusters in every self-reported health domain. Similarly, for both LBP and MBPNP, pain drawings involving more extensive pain areas were associated with higher activity limitation, more intense pain, and more psychological distress. This study presents a versatile data-driven approach for analyzing pain drawings to assist in managing spinal pain.

The legacy of Nizami Ganjavi in Transoxiana: An analysis of Khamsa's influence on oral narrative

Nizami Ganjavi, one of the distinguished poets of the 12th century, has a special place in world literature with his works from ancient times to the present. This poet is famous not only in Persian literature but also in Turkish and Indian literature. Nizami Ganjavi is related to the Mesnevi works, which were translated into Turkish and even translated by many Turkish poets and writers in the following centuries. Among these, we can count the essential figures of Chagatai Turkish literature (Transoxiana), especially Emir Alişer Nevai, who cared about Mesnevi Khamsa Nizami and made changes and wrote examples based on his stories. Nizâmî, with the dreams and images created in the Mesnevi above, has revealed an original style that is very important in today's comparative literature field at the international level. He proved his success by creating a new style of fantasy drawing using imaginary images, and many poets influenced by him entered the field of literature. This article refers to Panj Ganj or Khamsa Nizami Ganjavi's works and tries to explore his influence on Transoxiana writers. The study uses a qualitative, library, and comparative methodology and is founded on the laws and categories of scientific research. Researchers applied modern research approaches and methods (general scientific analysis, comparison, generalization, systematization, text analysis, and retrospective analysis).

CROSSOVER AND EXTENSION OF HAND-DRAWN MAP IN HERITAGE TOURISM: A CASE STUDY

In the realm of thematic map development, hand-drawn maps tailored for tourism hold considerable significance. Nonetheless, their progress is impeded by inherent limitations and challenges, thereby constraining their potential advancement. Concurrently, the emergence and progression of computer and network technology have furnished a proficient platform for fostering interdisciplinary growth in the realm of hand-drawn cartography. The aim of this study is establishing a customized, culturally relevant, metaphorical and de-identified design framework for enhancing visualization in digital interactions, drawing upon the universal design principles inherent in traditional animation. A comprehensive depiction of the design workflow, along with intricate design particulars pertaining to each stage, was demonstrated through a case study centered on the hand-drawn style drawing and map design for Dahuaishu Ancestor Memorial Garden. By adopting such a design framework, the potential outcome entails a more user-friendly and captivating means of disseminating information within digital tourist maps of the same genre. This approach preserves the inherent merits of hand-drawn maps while simultaneously broadening their scope and capabilities.

“The Right Despair”: Kafka’s Nihilist Technique

Kafka’s drawing style, like his writing one, is abstemious in the extreme; the question is how to characterize his criterion of subtraction. Studying the diary drawings alongside the text in which they are embedded points toward a general dynamic of deactivation—an aesthetics of disillusion in the baroque tradition of desengaño—that can be seen more clearly than read. Kafka repeatedly draws and writes about thresholds. But while his diary writing tends to thematize a perceived failure to pass from one side to another, the accompanying drawings systematically eliminate this register, and with it, all sense of directional movement or striving. The drawings operate as emblems of a passage, and so also of metapherein, in all its most iconic shapes—ladders, gates, permeable walls—but of a passage suspended at the very apex of its arc, where failure is impossible to distinguish from success. The nihilistic thrust of an aestheticized despair is here in turn negated, and the result, like Wittgenstein’s duck rabbit example, is in principle ambiguous. The essay argues that such structural ambiguity becomes a crucial feature of the literary works, which are constructed, as the diary entries themselves usually are not, in accordance with a similarly emblematic technique of double negation or “right despair.”

Isometric Digital Tourism Map as Sustainable Development of Bendosari Ecotourism Village

Bendosari Ecotourism Village development can be carried out by preparing various necessary needs, such as creating visual communication design media for them, such as digital maps. Tourists need complete information about tourist attractions before visiting the location to prepare various equipment, especially new ones. There needs to be promotional support media that collaborates with technology so that conveying information to tourists is easier and more efficient. This research designs a digital tourist map for Bendosari Ecotourism Village to introduce local Indonesian tourism using design thinking methods and creating digital tourist maps. This design results in a digital tourist map using a flat vector drawing style and coloured isometric illustrations easily accessible with barcodes. The digital tourist map of Bendosari Ecotourism Village displays the existing and most potential tourist locations to be introduced to the Indonesian people. People can easily walk around the Bendosari Ecotourism Village to enjoy every tourist spot. These findings help promote the Bendosari Ecotourism Village to the Indonesian people.

Mitigating Viewer Impact From Disturbing Imagery Using AI Filters: A User-Study

Exposure to disturbing imagery can significantly impact individuals, especially professionals who encounter such content as part of their work. This article presents a user study, involving 107 participants, predominantly journalists and human rights investigators, that explores the capability of Artificial Intelligence (AI)-based image filters to potentially mitigate the emotional impact of viewing such disturbing content. We tested five different filter styles, both traditional (Blurring and Partial Blurring) and AI-based (Drawing, Colored Drawing, and Painting), and measured their effectiveness in terms of conveying image information while reducing emotional distress. Our main findings suggest that the AI-based Drawing style filter demonstrates the best performance, offering a promising solution for reducing negative feelings (−30.38%) while preserving the interpretability of the image (97.19%). Overall, this article contributes to the development of a more ethically considerate and effective visual environment for professionals routinely engaging with potentially disturbing imagery.

A Fourier neuromorphic visual system based on InGaZnO synaptic transistor

The hierarchical structure of the biological visual system enables multilevel features of sensory stimuli to be pre-extracted before being transmitted to the nerve center, rendering the remarkable ability to perceive, filter, categorize, and identify targets in complex environments. However, it is a challenge to resemble such extraction capability with respect to spatial features in a neuromorphic visual system. In this Letter, we propose an indium-gallium-zinc-oxide synaptic transistor-based Fourier neuromorphic visual system for image style classifying. The images are transformed into the frequency domain through an optic Fourier system, greatly reducing energy and time dissipation in comparison with numerical computation. Then, the transformed information is coded into spike trains, which are nonlinearly filtered by synaptic transistors. The energy consumption for this filtering process is estimated to be ∼1.28 nJ/pixel. The features of drawing style could be enhanced through the filtering process, which facilitates the followed pattern recognition. The recognition accuracy in classifying stylized images is significantly improved to 92% through such Fourier transform and filtering process. This work would be of profound implications for advancing neuromorphic visual system with Fourier optics enhanced feature extraction capabilities.

ONOMOTOPEIA AS A MEANS OF EXPRESSIVENESS IN A GRAPHIC NOVEL: SOME NUANCES OF TRANSLATION

The article is devoted to onomatopoeia as a means of expressiveness in a graphic novel, to be precise, to the peculiarities of the translation of onomatopoeic words from French into Ukrainian. The purpose of the study is to find out the characteristic traits of onomatopoeia in a graphic novel and analyze its translation strategies, compiling a mini-dictionary of onomatopoeias (language pair French — Ukrainian). In the course of the research, it was found that the graphic novel relies on a purely visual and textual component. It is the visual accompaniment of colors, text and drawing style that helps to understand how to perceive onomatopoeia in context. Such an artistic tool as a speech bubble is also responsible for conveying the meaning of onomatopoeia, so the shape, size, and style of letters must be taken into account during interpretation. When working on the translation of onomatopoeia in graphic novels, it is necessary to rely on general linguistic knowledge, analyzing the type of onomatopoeia by origin (human sounds, animal sounds, nature sounds, sounds of objects) and the meaning of formative onomatopes for a more effective selection of analogues. At the same time, the process of translation is primarily a creative process, so it is impossible to offer a specific model of work on the text. Having studied the ways of translating onomatopoeia in a number of comics about Tintin (Hergé) and in “Persepolis” (Marjan Satrapi), we came to the conclusion that the translators used the following strategies: transcription / transliteration; partial adaptation (replacement of one or two letters); complete replacement of the onomatopoeic word with a word specific to the Ukrainian language; full replacement of the word with partial replacement of the meaning; replacing the onomatopoeia with the root of the corresponding verb. Common in translation practice is the addition and removal of certain elements (onomatopoeia included), which is generally not approved, but is not a drawback provided that the author’s intention is followed. Often the translator has to combine strategies to achieve an accurate and expressive result.

Top-down generation of low-resolution representations improves visual perception and imagination

Perception or imagination requires top-down signals from high-level cortex to primary visual cortex (V1) to reconstruct or simulate the representations bottom-up stimulated by the seen images. Interestingly, top-down signals in V1 have lower spatial resolution than bottom-up representations. It is unclear why the brain uses low-resolution signals to reconstruct or simulate high-resolution representations. By modeling the top-down pathway of the visual system using the decoder of a variational auto-encoder (VAE), we reveal that low-resolution top-down signals can better reconstruct or simulate the information contained in the sparse activities of V1 simple cells, which facilitates perception and imagination. This advantage of low-resolution generation is related to facilitating high-level cortex to form geometry-respecting representations observed in experiments. Furthermore, we present two findings regarding this phenomenon in the context of AI-generated sketches, a style of drawings made of lines. First, we found that the quality of the generated sketches critically depends on the thickness of the lines in the sketches: thin-line sketches are harder to generate than thick-line sketches. Second, we propose a technique to generate high-quality thin-line sketches: instead of directly using original thin-line sketches, we use blurred sketches to train VAE or GAN (generative adversarial network), and then infer the thin-line sketches from the VAE- or GAN-generated blurred sketches. Collectively, our work suggests that low-resolution top-down generation is a strategy the brain uses to improve visual perception and imagination, which inspires new sketch-generation AI techniques.

PERANCANGAN ILUSTRASI GERAK BERGAYA GAMBAR SEMI REALIS SEBAGAI TEROBOSAN PRODUK BARU FARARAFA STUDIO

This study discusses how to design motion illustrations with a semi-realist art style as a new product breakthrough for Fararafa Studio. The product in this study is an updated design from the previous product, namely an illustration image with a JPG extension. The purpose of this research is to produce a work process that can underlie the production process of motion illustrations with GIF and MP4 output as a product sample for Fararafa Studio and to test the feasibility of the illustration products that have been made by researchers. Using a Research and Development Methodology whose application is very suitable for testing the effectiveness of products with various stages and validations. The illustration will use a semi-realist drawing style because this semi-realist illustration product is the most sought after by Fararafa Studio's clients. The image process will use Adobe Photoshop software, then be animated using Adobe After Effects.

Creating Personal Expressions In Expanded Drawing Artworks Through A Synectic Approach

Expanded drawing is an investigation of the evolution of drawing techniques and media/materials that have given artists the freedom to experiment, venture outside of their comfort zones, and change their routines. Extended drawing offers difficult activity engagements by fusing media and techniques with imaginative concepts. It also expands and reframes traditional drawing disciplines and approaches to produce works with a vibrant, modern personality. To create works that allude to distinctive traits and processes, media and technique development is done while keeping a larger context in mind. New media or media that has been used frequently are both used in this process. With its ability to create a dynamic and imaginative arena, Drawing Expanded is full of exploration, responding to medium and drawing styles in accordance with the concept being created. Expanded drawing is a new definition that arises from redefining, based on the individual's choice of media and technique as well as the environment. American artist Robert Morris first used the word in 1946 to describe a three-dimensional approach outside galleries that highlighted the value of creative exploration and interaction with materials, media, techniques, locations, and ideas.

Efficient Interpolation of Rough Line Drawings

AbstractIn traditional 2D animation, sketches drawn at distant keyframes are used to design motion, yet it would be far too labor‐intensive to draw all the inbetween frames to fully visualize that motion. We propose a novel efficient interpolation algorithm that generates these intermediate frames in the artist's drawing style. Starting from a set of registered rough vector drawings, we first generate a large number of candidate strokes during a pre‐process, and then, at each intermediate frame, we select the subset of those that appropriately conveys the underlying interpolated motion, interpolates the stroke distributions of the key drawings, and introduces a minimum amount of temporal artifacts. In addition, we propose quantitative error metrics to objectively evaluate different stroke selection strategies. We demonstrate the potential of our method on various animations and drawing styles, and show its superiority over competing raster‐ and vector‐based methods.

Unsupervised Portrait Drawing Generation for Free Styles

Artistic portrait drawing (APDrawing) generation has seen progress in recent years. However, due to the naturally high scarcity and artistry, it is difficult to collect large-scale labeled and paired data and generally divide drawing styles into several specific recognized categories. Existing works suffer from the limited labeled data and naive manual division of drawing styles according to the corresponding artists. They cannot adapt to the actual situations, for example, a single artist might have multiple drawing styles and APDrawings from different artists might share similar styles. In this paper, we propose to use unlabeled and unpaired data and perform the task in an unsupervised manner. Without manual division of drawing styles, we take each portrait drawing as a unique style and introduce self-supervised feature learning to learn free styles for unlabeled portrait drawings. Besides, we devise a style bank and a decoupled cycle structure to take over two main considerations in the task: generation quality and style control. Extensive experiments show that our model is more adaptable to different style inputs than state-of-the-art methods.

Collar recognition and matching of clothing style drawings based on complex networks

Seeking a fast and effective algorithm for describing and classifying clothing styles is currently a hot topic in the textile and clothing industry. The study first constructs a sample library of collar styles, preprocesses clothing images, and uses complex network models to describe and extract features; Implement clothing image classification based on support vector machines, and finally use image matching algorithms to match the image to be matched with the target object. It was indicated that the complex network model established by the research institute can effectively depict the characteristics of various collar styles, and the complex network model can effectively depict the characteristics of various collar styles. In 10 experiments, the overall average overall accuracy was 98%; Regarding different types of collars, the average accuracy of 10 experiments is above 96%, indicating that the collar classification accuracy based on support vector machine method is very high. The classifying results of the 10 categories obtained by the research method have little change and are relatively stable. For each category, the research method is higher than the other two methods. The results can indicate that the research method has effect and is more suitable for collar recognition and classification. Compared with traditional Hu invariant moments and HOG feature extraction algorithms, the research algorithm has stronger noise suppression ability, and using Euclidean distance as a similarity measure has great advantages.

Stylistic co-existence and the chronotope in Stone Fruit and onwards towards our noble deaths

ABSTRACT In this essay, I will examine the co-existence of different styles of drawing in Stone Fruit by Lee Lai (Lai, 2021). I will argue that this graphic novel uses two styles of drawing to produce different space times which can be better understood through a discussion of Bakhtin’s idea of the Chronotope. (Bakhtin 2011) I will compare this use of drawing to the drawing styles present in Onwards Towards Our Noble Deaths by Shigeru Mizuki (Mizuki and Allen, 2011) and argue that these comics use style to activate different chronotopic space times in order to deepen the reader's understanding of the interpersonal relationships between characters. I will consider the implications for both the drawn and drawing body in these comics, in the context of the history of naturalistic forms of representational drawing in manga and the practice of genre-splicing and ‘swiping’ in alternative comics. I will examine ways in which the movement between two styles of drawing form a structuring element of these narratives and argue that this movement is essential to communicating the meaning of these comics.

Semi-supervised reference-based sketch extraction using a contrastive learning framework

Sketches reflect the drawing style of individual artists; therefore, it is important to consider their unique styles when extracting sketches from color images for various applications. Unfortunately, most existing sketch extraction methods are designed to extract sketches of a single style. Although there have been some attempts to generate various style sketches, the methods generally suffer from two limitations: low quality results and difficulty in training the model due to the requirement of a paired dataset. In this paper, we propose a novel multi-modal sketch extraction method that can imitate the style of a given reference sketch with unpaired data training in a semi-supervised manner. Our method outperforms state-of-the-art sketch extraction methods and unpaired image translation methods in both quantitative and qualitative evaluations.

Feature-preserving color pencil drawings from photographs

Color pencil drawing is well-loved due to its rich expressiveness. This paper proposes an approach for generating feature-preserving color pencil drawings from photographs. To mimic the tonal style of color pencil drawings, which are much lighter and have relatively lower saturation than photographs, we devise a lightness enhancement mapping and a saturation reduction mapping. The lightness mapping is a monotonically decreasing derivative function, which not only increases lightness but also preserves input photograph features. Color saturation is usually related to lightness, so we suppress the saturation dependent on lightness to yield a harmonious tone. Finally, two extremum operators are provided to generate a foreground-aware outline map in which the colors of the generated contours and the foreground object are consistent. Comprehensive experiments show that color pencil drawings generated by our method surpass existing methods in tone capture and feature preservation.