85 research outputs found

    Visualizing situations: comparing pixel and vector art style in a dining situation sketch

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    Previous study indicated that the simplicity of a visualized situation could play an important role in comprehension and emotion. However, the effect of the art style was never discussed. As an art style with minimalist aesthetic, pixel art’s popularity and value are not well explained. This study is aimed to investigate the difference between pixel and vector art style by comparing one of the visualized situations extracted from previous study and the pixelated counterpart. 166 valid responses were collected (69 males & 97 females). Participants were randomly separated into 2 groups, presented with 2 different art styles. After observing the visualized situation, they filled in a questionnaire asking about their understandings, evoked emotions, how realistic it feels, and how easy for them to picture themselves in the situation. ANOVAs and multiple regression analyses were conducted and results showed that art style did not have a big impact on emotions, whereas for pixel art style, the older the participant is, the easier they could picture themselves being in the situation. Additional analysis using chi-square test found that people tend to believe the situation is in a past era when observing the pixel version. This study revealed the potential impact of pixel art style on people’s comprehension, tricking people to believe it is happening in a past era. This phenomenon should be taken advantage of in not only game design but also other media graphic design scenarios

    VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models

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    Diffusion models have shown impressive results in text-to-image synthesis. Using massive datasets of captioned images, diffusion models learn to generate raster images of highly diverse objects and scenes. However, designers frequently use vector representations of images like Scalable Vector Graphics (SVGs) for digital icons or art. Vector graphics can be scaled to any size, and are compact. We show that a text-conditioned diffusion model trained on pixel representations of images can be used to generate SVG-exportable vector graphics. We do so without access to large datasets of captioned SVGs. By optimizing a differentiable vector graphics rasterizer, our method, VectorFusion, distills abstract semantic knowledge out of a pretrained diffusion model. Inspired by recent text-to-3D work, we learn an SVG consistent with a caption using Score Distillation Sampling. To accelerate generation and improve fidelity, VectorFusion also initializes from an image sample. Experiments show greater quality than prior work, and demonstrate a range of styles including pixel art and sketches. See our project webpage at https://ajayj.com/vectorfusion .Comment: Project webpage: https://ajayj.com/vectorfusio

    Pixelating Vector Art

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    Pixel art is a popular style of digital art often found in video games. It is typically characterized by its low resolution and use of limited colour palettes. Pixel art is created manually with little automation because it requires attention to pixel-level details. Working with individual pixels is a challenging and abstract task, whereas manipulating higher-level objects in vector graphics is much more intuitive. However, it is difficult to bridge this gap because although many rasterization algorithms exist, they are not well-suited for the particular needs of pixel artists, particularly at low resolutions. In this thesis, we introduce a class of rasterization algorithms called pixelation that is tailored to pixel art needs. We describe how our algorithm suppresses artifacts when pixelating vector paths and preserves shape-level features when pixelating geometric primitives. We also developed methods inspired by pixel art for drawing lines and angles more effectively at low resolutions. We compared our results to rasterization algorithms, rasterizers used in commercial software, and human subjects---both amateurs and pixel artists. Through formal analyses of our user study studies and a close collaboration with professional pixel artists, we showed that, in general, our pixelation algorithms produce more visually appealing results than na\"{i}ve rasterization algorithms do

    “I Don’t Want to Become a Number’’: Examining Different Stakeholder Perspectives on a Video-Based Monitoring System for Senior Care with Inherent Privacy Protection (by Design)

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    Active and Assisted Living (AAL) technologies aim to enhance the quality of life of older adults and promote successful aging. While video-based AAL solutions offer rich capabilities for better healthcare management in older age, they pose significant privacy risks. To mitigate the risks, we developed a video-based monitoring system that incorporates different privacy-preserving filters. We deployed the system in one assistive technology center and conducted a qualitative study with older adults and other stakeholders involved in care provision. Our study demonstrates diverse users’ perceptions and experiences with video-monitoring technology and offers valuable insights for the system’s further development. The findings unpack the privacy-versus-safety trade-off inherent in video-based technologies and discuss how the privacy-preserving mechanisms within the system mitigate privacy-related concerns. The study also identifies varying stakeholder perspectives towards the system in general and highlights potential avenues for developing video-based monitoring technologies in the AAL context.This work was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 861091 for the visuAAL project. This publication is based upon work from COST Action GoodBrother—Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living (CA19121), supported by COST (European Cooperation in Science and Technology)

    Visual Privacy Protection Methods: A Survey

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    Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual’s privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users’ acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people’s privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U - A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649). José Ramón Padilla López and Alexandros Andre Chaaraoui acknowledge financial support by the Conselleria d'Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2012/064 and ACIF/2011/160 respectively)

    Bayesian Strong Gravitational-Lens Modeling on Adaptive Grids: Objective Detection of Mass Substructure in Galaxies

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    We introduce a new adaptive and fully Bayesian grid-based method to model strong gravitational lenses with extended images. The primary goal of this method is to quantify the level of luminous and dark-mass substructure in massive galaxies, through their effect on highly-magnified arcs and Einstein rings. The method is adaptive on the source plane, where a Delaunay tessellation is defined according to the lens mapping of a regular grid onto the source plane. The Bayesian penalty function allows us to recover the best non-linear potential-model parameters and/or a grid-based potential correction and to objectively quantify the level of regularization for both the source and the potential. In addition, we implement a Nested-Sampling technique to quantify the errors on all non-linear mass model parameters -- ... -- and allow an objective ranking of different potential models in terms of the marginalized evidence. In particular, we are interested in comparing very smooth lens mass models with ones that contain mass-substructures. The algorithm has been tested on a range of simulated data sets, created from a model of a realistic lens system. One of the lens systems is characterized by a smooth potential with a power-law density profile, twelve include a NFW dark-matter substructure of different masses and at different positions and one contains two NFW dark substructures with the same mass but with different positions. Reconstruction of the source and of the lens potential for all of these systems shows the method is able, in a realistic scenario, to identify perturbations with masses >=10^7 solar mass when located on the Einstein ring. For positions both inside and outside of the ring, masses of at least 10^9 solar mass are required (...).Comment: 21 pages, 15 figures, 4 tables; accepted for publication in MNRA

    Eco-energy Smart Card”: A human-interactive all paper based, mechanical energy harvester

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    Nowadays, it is imperative that modern society finds sustainable ways to harvest energy. This means society is forced to look to new ways to generate and store energy, while reducing, simultaneously, the stress on raw materials demand and the amount of waste generated. Our research tackles these two points by making close to zero e-waste clean energy harvesting devices. The core idea behind it is based on the mechano-responsive charge-transfer mechanism and energy-transfer process in π-conjugated polymer at the organic-metal interface layer. A localized forced deformation of the interface has been applied against the polymer surface, allowing charge transfer between material interfaces. The experimental results demonstrated that during contacting force, the conjugated polymer film shows electrical output through the charge transfer mechanism within metal/polymer interfaces. Flexible and low-cost energy harvesting devices built have an active layer constituted by a PANi/cellulose composite which was tapped together to a charge collector layer, that was made from a paper based metallic electrode. These devices have a total maximum power density and maximum current density of 1.75 Wm-2 and 33.5 mA m-2 , respectively. Towards the practical applicability, these devices are able to light up to 40 blue LEDs as well as a commercial humidity sensor

    Pembentukan Pola Desain Motif Karawo Gorontalo Menggunakan K-Means Color Quantization dan Structured Forest Edge Detecion

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    Sulaman Karawo merupakan kerajinan tangan berupa sulaman khas dari daerah Gorontalo. Motif sulaman diterapkan secara detail berdasarkan suatu pola desain tertentu. Pola desain digambarkan pada kertas dengan berbagai panduannya. Gambar yang diterapkan pada pola memiliki resolusi sangat rendah dan harus mempertahankan bentuknya. Penelitian ini mengembangkan metode pembentukan pola desain motif Karawo dari citra digital. Proses dilakukan dengan pengolahan awal menggunakan k-means color quantization (KMCQ) dan deteksi tepi structured forest. Proses selanjutnya melakukan pengurangan resolusi menggunakan metode pixelation dan binarization. Luaran dari algoritma menghasilkan 3 citra berbeda dengan ukuran yang sama, yaitu: citra tepi, citra biner, dan citra berwarna. Ketiga citra tersebut selanjutnya dilakukan proses pembentukan pola desain motif Karawo dengan berbagai petunjuk pola bagi pengrajin. Hasil menunjukkan bahwa pola desain motif dapat digunakan dan dimengerti oleh para pengrajin dalam menerapkannya di sulaman Karawo. Pengujian nilai-nilai parameter dilakukan pada metode k-means, gaussian filter, pixelation, dan binarization. Parameter-parameter tersebut yaitu: k pada k-means, kernel pada gaussian filter, lebar piksel pada pixelation, dan nilai threshold pada binarization. Pengujian menunjukkan nilai terendah tiap parameter adalah k=4, kernel=3x3, lebar piksel=70, dan threshold=20. Hasil memperlihatkan makin tinggi nilai-nilai tersebut maka semakin baik pola desain motif yang dihasilkan. Nilai-nilai tersebut merupakan nilai parameter terendah dalam pembentukan pola desain motif berkualitas baik berdasarkan indikator-indikator dari desainer. AbstractKarawo embroidery is a unique handicraft from Gorontalo. The embroidery motif is applied in detail based on a certain design pattern. These patterns are depicted on paper with various guides. The image applied to the pattern is very low resolution and retains its shape. This study develops a method to generate a Karawo design pattern from a digital image. The process begins by using k-means color quantization (KMCQ) to reduce the number of colors and edge detection of the structured forest. The next process is to change the resolution using pixelation and binarization methods. The output algorithm produces 3 different state images of the same size, which are: edge image, binary image, and color image. These images are used in the formation of the Karawo motif design pattern. The motif contains various pattern instructions for the craftsman. The results show that it can be used and understood by the craftsmen in its application in Karawo embroidery. Testing parameter values on the k-means method, Gaussian filter, pixelation, and binarization. These parameters are k on KMCQ, the kernel on a gaussian filter, pixel width in pixelation, and threshold value in binarization. The results show that the lowest value of each parameter is k=4, kernel=3x3, pixel width=70, and threshold=20. The results show that the higher these values, the better the results of the pattern design motif. Those values are the lower input to generate a good quality pattern design based on the designer’s indicators
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