Visual Filters Research Articles

Children in sync: exploring how interpersonal synchrony experience induces cooperation between child peers

Synchronous interpersonal movements induce positive prosocial behaviors in adults and children. The processes that underlie this are debated. Here, we investigate the extent to which visual cues available during synchrony experience—particularly shared facial expressions and mutual eye contact—are necessary. Pairs of same-sex 4-year-olds (N = 216 children; 50% girls; 81% white) from the US were randomly assigned to synchronized versus asynchronized swinging experience. Access to visual information was experimentally manipulated by using a transparent versus translucent barrier between the children. The translucent barrier acted as a visual filter preventing children from monitoring facial cues while still enabling them to see whether the partner was swinging in synchrony. After the swinging experience, all pairs of children were administered the same tests of cooperation. The children administered synchronous movement performed better on the cooperation tasks, and there was no significant difference as a function of barrier transparency. This suggests that the positive effects of synchrony do not require visual resolution of the partner’s social-emotional facial cues. These findings advance our understanding about factors contributing to synchrony-induced cooperation between children.

Using deep learning to enhance electronic service quality: Application to real estate websites

Electronic service quality (E-SQ) is a strategic metric for successful e-services. Among the service quality dimensions, tangibility is overlooked. However, by incorporating visuals or tangible tools, the intangible nature of e-services can be balanced. Thanks to advancements in Deep Learning for computer vision, tangible visual features can now be leveraged to enhance the browsing and searching experience electronic services. Users usually have specific search criteria to meet, but most services won't offer flexible search filters. This research emphasizes the importance of integrating visual and descriptive features to improve the tangibility and efficiency of e-services. A prime example of an electronic service that can benefit from this is real-estate websites. Searching for real estate properties that match user preferences is usually demanding and lacks visual filters, such as the Damage Level to the property. The research introduces a novel visual descriptive feature, the Damage Level, which utilizes a deep learning network known as Mask-RCNN to estimate damage in real estate images. Additionally, a model is developed to incorporate the Damage Level as a tangible feature in electronic real estate services, with the aim of enhancing the tangible customer experience.

Biomaterial-Based Biomimetic Visual Sensors: Inkjet Patterning of Bacteriorhodopsin.

Biomimetic visual sensors utilizing bacteriorhodopsin (bR) were fabricated by using an inkjet method. The inkjet printer facilitated the jetting of the bR suspension, allowing for the deposition of bR films. The resulting inkjet-printed bR film exhibited time-differential photocurrent response characteristics similar to those of a dip-coated bR film. By adjusting the number of printed bR film layers, the intensity of the photocurrent could be easily controlled. Moreover, the inkjet printing technique enabled unconstrained patterning, facilitating the design of various visual information processing functions, such as visual filters. In this study, we successfully fabricated two visual filters, namely, a two-dimensional Difference of Gaussian (DOG) filter and a Gabor filter. The printed DOG filter demonstrated edge detection capabilities corresponding to contour recognition in visual receptive fields. On the other hand, the printed Gabor filter proved effective in detecting objects of specific sizes as well as their motion and orientation. The integration of bR and the inkjet method holds significant potential for the widespread implementation of highly functional biomaterial-based visual sensors. These sensors have the capability to provide real-time visual information while operating in an energy-efficient manner.

The TikTok Experience and Everything Everywhere All At Once: A Brief Analysis of Film Form

The TikTok experience refers to a user’s interaction with the platform while scrolling through various videos. The user can change what they are viewing instantly on one screen much like a TV viewer, the only difference being that whatever is being watched is in the form of short videos made specifically for the platform. These videos vary in style and form and are made to be viewed within the platform itself. All the content that a user watches within the mobile application, in the end, forms a longer, theoretically never-ending, video that is sometimes completely unrelated but more often similar through shared jokes, memes, and visual filters. This way of producing and viewing short-form videos as a whole is reminiscent of the way Everything Everywhere All At Once feels to the audience which is no surprise as many other forms of media and artworks are inspired by internet short-form video platforms such as TikTok.

An investigation into the effect of exposing XMM–Newton’s Optical Monitor to the light of Jupiter

Abstract After nearly 18 yr of successful and safe operations, on 2017 July 17 and 18, XMM–Newton’s Optical Monitor (OM) observed Jupiter – an object 10 magnitudes brighter than safe brightness limits – in its visual (V) filter. The object was exposed 40 arcsec from the nominal European Photon Imaging Cameras pn boresight in the negative Y direction, creating a patch of depleted sensitivity. Two exposures of 4000 s each in the V filter left the sensitivity depleted in an area 70 by 40 arcsec; with the decrease in throughput varying from 34 per cent in the V filter to 15 per cent in the ultraviolet bands, but reaching a depth of 45 per cent in flat-field exposures. The wavelength dependency suggests the majority of the detector damage is due to loss of sensitivity in the photocathode from damage inflicted by ion feedback, while up to 15 per cent could be due to gain depletion of the MCP. The physical mechanisms causing the damage to the detector are discussed as well as possible solutions and opportunities that exist for the future operation of the OM.

Classification of objects and scenes by a neural network with pretrained input modules to decode spatial texture inhomogeneities

Subject of study. The study investigated the possibility of using neural network models of second-order visual mechanisms as inputs for neural network classifiers. Second-order visual mechanisms can detect spatial inhomogeneities in the contrast, orientation, and spatial frequency of an image. These mechanisms are traditionally considered one of the stages of early visual processing; their role in the perception of textures has been well studied. Aim of study. The study aimed to investigate whether the use of classifier input modules pretrained to demodulate the spatial modulations of luminance gradients contributed to object and scene classifications. Method. Neural network modeling was used as the main method. At the first stage of the study, a set of texture images was generated to train neural network models of second-order visual mechanisms. At the second stage, the object and scene samples were prepared, based on which classifier networks were trained. Pretrained models of second-order visual mechanisms with fixed weights were applied as these network inputs. Main results. The second-order information presented as a map of instantaneous values of the modulation function of contrast, orientation, and spatial frequency of the image was sufficient for the identification of only some of the scene classes. In general, the use of the values of luminance gradient modulation functions for object classification proved to be ineffective within the proposed neural network architectural framework. Thus, the hypothesis stating that second-order visual filters encode features enabling the identification of objects was not confirmed. This result makes it necessary to test an alternative hypothesis stating that the role of second-order filters is limited to the construction of saliency maps, and filters are windows through which information is received from the first-order filter outputs. Practical significance. The possibility of using second-order models of visual mechanisms in computer vision systems was assessed.

The “Fox Eye” Challenge Trend: Anti-Racism Work, Platform Affordances, and the Vernacular of Gesticular Activism on TikTok

This article takes the “Fox Eye” challenge that trended on social media in 2020 as a case study in anti-racism activism by (East) Asian users on TikTok. The “Fox Eye” challenge was a trend in which both celebrities and ordinary users—often predominantly White women—posted photos and short videos on how to wear specific styles of make-up to achieve almond-shaped eyes or “fox eyes.” This was often accompanied with a “migraine pose” where a user pushes their index and middle fingers up against the temples on both sides of their head to “lift” the corners of their upper eyelids, and was colloquially referred to as a “Chinese” or “oriental” look. In response, (East) Asian users on TikTok called out the historically racist undertones of this seemingly superficial trend, using the features and affordances of the platform to produce everyday, nonheroic forms of digital activism, as an act of civic engagement and activist campaigning. Building on the scholarship on digital activism, we consider how TikTok has emerged as an alternative activist space for young people, specifically as it services users as a video production and sharing app. We specifically focus on the audiovisual aesthetics of the TikTok narratives in the counter-Fox Eye trend campaign, wherein the strategic and templatable deployments of vernacular TikTok aesthetics—curated image selections, creative uses of sound and audio memes, specific renders of visual filters and effects—play a central role in giving meaning to the online activist narratives created. This has given rise to platformed activism in the TikTok vernacular that we term “gesticular activism,” which focuses on the generation of visibility and virality as awareness-building and consciousness-raising tactics.

SECOND-ORDER VISUAL MECHANISMS: REVIEW OF RESEARCH

The review is devoted to the analysis of studies aimed at studying second-order visual filters as a mechanism for preattentive grouping of local visual information by striate neurons (first-order filters). The development of ideas about possible mechanisms for combining primary visual features is analyzed, with the emphasis on studies of the properties of second-order filters. The questions of spatial organization and principles of interaction of filters of the first and second orders are considered. The results indicating the multichannel nature of the pooling mechanism and possible relationship between the frequency and orientation settings of the filters of the first and second order are described. A model for organizing filters of the second order is presented, possible neurophysiological correlates of these mechanisms are analyzed, role of the second-order mechanisms in visual perception is considered.

FQA-Net: an efficient neural network for blind image quality assessment

Guided by the neural network (NN), NN-based blind image quality assessment (BIQA) methods have improved image quality prediction accuracy. However, the training process of NN will consume a lot of time and training data. To solve the above problems, an efficient NN structure, which is called fast quality assessment network (FQA-Net), is proposed for BIQA. FQA-Net is a very simple NN, which mainly includes a convolution layer, a standard deviation measurement layer, and a regression layer. The convolution kernels in the convolution layer are a set of visual filters with characteristics of visual neurons, which are obtained by training on natural image samples. The output of the convolutional layer is a set of feature maps. Then the standard deviation of each feature map is calculated directly. Finally, a regression model is used for the mapping between the standard deviation values and the quality scores. FQA-Net not only reduces the number of parameters and the output dimensions in the training process, but also prevents network overfitting effectively. The results on seven image databases (i.e., LIVE, CSIQ, TID2013, LIVEMD, KADID-10K, LIVEC, and KonIQ-10K) show that FQA-Net has relatively low computational complexity and high computational speed and accuracy compared with other leading BIQA methods, especially when the number of training samples is very low. Moreover, the FQA-Net can provide stable prediction results across different distortion types.

Vision Processing for Assistive Vision: A Deep Reinforcement Learning Approach

There is increasing interest in using computer vision and machine learning to enhance human decision making with computer-mediated assistive vision systems. In particular, retinal implants are a rapidly advancing technology offering individuals suffering vision loss due to retinal dystrophies, an opportunity to restore partial vision. However, the visual representations achievable with current and near-term implants are severely limited in resolution and contrast, placing high importance on the selection of visual features to convey via the implant. Using vision processing algorithms on camera-captured input, functional outcomes can be enhanced with such devices. To this end, we propose a novel end-to-end vision processing pipeline for prosthetic vision that learns task-salient visual filters in simulation offline via deep reinforcement learning (DRL). Once learnt, these filters are deployable on a prosthetic vision device to process camera-captured images and produce task-guiding scene representations in real-time. We show how a set of learnt visual features enabling a virtual agent to optimally perform the task of navigation in a 3-D environment can be extracted and applied to enhance the same features in real world images. We evaluate and validate our proposed approach quantitatively and qualitatively using simulated prosthetic vision. To our knowledge, this is the first application of DRL to the derivation of scene representations for human-centric computer-mediated displays such as prosthetic vision devices.

TIKTOK’S ‘FOX EYE’ TREND AND EVERYDAY ACTIVISM: GEN Z AGENCY IN AN AUDIOVISUAL NARRATIVE CASE STUDY

This paper examines TikTok as an emerging activist space for Gen Z. It uses the ‘fox eye’ trend as a case study to illustrate how TikTok allows young people – Asian diasporic communities in particular – to create audiovisual narratives of personal experiences and stories to speak up against anti-Asian racism. Through a qualitative content analysis of 30 relevant TikTok posts, the paper argues for the platform’s distinct audiovisual features in enhancing users’ capacity for civic engagement. This paper generates three related findings. First, young Asian users have created TikTok videos featuring a variety of themes in relation to the fox eye trend. Some notable examples include historical popular representation of Asians, personal experiences of racism, impossible beauty standards, jokingly advocating for countertrends, among others. Collectively, these videos aim to emphasize the ‘problems’ associated with the trend – that is, it is racially insensitive and builds on cultural appropriation. The second finding suggests three main types of narratives constructed through the videos – historical, educational and affective. Each type is characterized by distinct narrative structures and strategies. Finally, the audiovisual functions of the platform in creating and amplifying the narratives. That is, the narratives on TikTok are powerful not only because of the rhetorical devices used, but also due to their audiovisual elements such as visual filters, audio memes, image and video compilations and non-verbal performance. Through these discussions of findings, we propose and explain the concept of ‘audiovisual narrative agency’ as an emerging lens to understand contemporary digital activism.

Modelling the visual world of a velvet worm.

In many animal phyla, eyes are small and provide only low-resolution vision for general orientation in the environment. Because these primitive eyes rarely have a defined image plane, traditional visual-optics principles cannot be applied. To assess the functional capacity of such eyes we have developed modelling principles based on ray tracing in 3D reconstructions of eye morphology, where refraction on the way to the photoreceptors and absorption in the photopigment are calculated incrementally for ray bundles from all angles within the visual field. From the ray tracing, we calculate the complete angular acceptance function of each photoreceptor in the eye, revealing the visual acuity for all parts of the visual field. We then use this information to generate visual filters that can be applied to high resolution images or videos to convert them to accurate representations of the spatial information seen by the animal. The method is here applied to the 0.1 mm eyes of the velvet worm Euperipatoides rowelli (Onychophora). These eyes of these terrestrial invertebrates consist of a curved cornea covering an irregular but optically homogeneous lens directly joining a retina packed with photoreceptive rhabdoms. 3D reconstruction from histological sections revealed an asymmetric eye, where the retina is deeper in the forward-pointing direction. The calculated visual acuity also reveals performance differences across the visual field, with a maximum acuity of about 0.11 cycles/deg in the forward direction despite laterally pointing eyes. The results agree with previous behavioural measurements of visual acuity, and suggest that velvet worm vision is adequate for orientation and positioning within the habitat.

FlexiSee: flexible configuration, customization, and control of mediated and augmented vision for users of smart eyewear devices

Smart eyewear and Augmented Reality technology have been examined closely in the scientific community to provide vision rehabilitation to people with visual impairments as well as augmented vision to people with and without visual impairments for various application scenarios and contexts of use. However, current systems lack flexibility in the configuration and customization of the features and functionalities they present to their users, as we show in this paper by means of a thorough literature review and categorization of prior work on augmented and mediated vision for smart eyewear devices. To address the flexibility aspect that has been missing in prior work, we introduce FlexiSee, an application for smart eyewear devices, such as see-through Augmented Reality glasses and Head-Mounted Mixed Reality Displays, specifically designed to enable flexible configuration, customization, and control of both augmented and mediated vision. FlexiSee achieves this desiderata by implementing visual filters (e.g., color correction, edge highlighting, contrast adjustment, and others) that are coupled with a web-based interface, readily accessible from smartphones, tablets, smartwatches, and other devices with web browsers, where authorized users can specify and apply custom parameters for the visual filters implemented by FlexiSee. We also introduce FlexiSee-DS, a three-dimensional design space for FlexiSee-like applications, that includes mediation & augmentation, user categories, and control design dimensions to specify a variety of FlexiSee-like systems. We show how the dimensions of FlexiSee-DS were applied to inform the design of our FlexiSee system, and we highlight and focus on the distinction between primary users and vision monitors and assistants, where the latter two categories represent new types of users for augmented and mediated vision that have various degrees of control, from their remote locations, over the visual reality delivered to and perceived by the primary users of smart eyewear devices. We conduct a user study to understand the perception of vision monitors and assistants regarding our new FlexiSee concept and system, and we report empirical results about usability aspects (e.g., we found an average SUS score of 75.3 and high ratings for the perceived usefulness of FlexiSee) as well as user feedback and suggestions to inform further developments of FlexiSee-like systems and applications.

Period of Eclipsing Binary EPIC 201458798

In this study we observed and determined the period of the eclipsing binary star EPIC 201458798, finding that its period has not changed since it was last measured and published in the Kepler catalog in 2014. We did this by developing Python code to determine the period using two independent algorithms and partially automating the search for suitable comparison stars. Our system was imaged by the 0.4m Las Cumbres Observatory telescopes in four filters. We analyzed six photometry types returned for each image from the Our Solar Siblings pipeline. Of these photometries, we found source extractor kron (sek) to be the most appropriate type for our 2x2 binned images of EPIC 201458798. Both of the period-finding algorithms we developed gave results that were not statistically different from the Kepler catalog period for the infrared, red, and visual filter images. The blue filter images were statistically different fromthe Kepler catalog period for one of our algorithms but not the other. 

As If out of a Goya Painting. Experiencing the past in Francoist Spain

This article deals with overlooked interactions between art history and colonial discourses within the context of tourism in Spain. It aims to demonstrate the central role played by temporalized narratives of otherness in tourist imaginaries about Spain during the 1950s and 1960s. It focusses on the use of art history as a visual filter through which certain aspects of the country were read and experienced as being stranded in the past, often leading to images of poverty becoming aestheticized. This analysis will throw light on how colonial discourses of temporality and authenticity, rather than ideas of modernization, influenced the international rehabilitation of the Franco dictatorship after the Second World War.

Without a blink: Machine ways of seeing in contemporary visual culture

In the last decade following the technological and commercial advances in digital image production and in artificial intelligence, human vision-centred understanding of visuality has changed profoundly. Machine vision technologies (MVTs) are used across a wide spectrum of activities ranging from surveillance to medical diagnosis, to adaptive visual filters on social media. This commentary calls for a rethinking of visuality that takes both technological advances and lessons learned from cultural studies into consideration.

Конкуренция за внимание пространственных модуляций градиентов яркости

Введение. Преаттентивный этап зрительной обработки включает стадию выделения и кодирования градиентов яркости, а также стадию пространственного объединения этой информации. Первая операция реализуется зрительными фильтрами первого порядка (стриарными нейронами), вторая – фильтрами второго порядка (экстрастриарными нейронами). Фильтры второго порядка пропускают области изображения, характеризующиеся наличием пространственных модуляций контраста, ориентации и пространственной частоты (размерности модуляции) и могут играть роль ворот внимания. Целью исследования является установление приоритетов среди модуляций в конкуренции за внимание.
 Методы. Все стимулы состояли из трех изображений одного и того же объекта. Эти изображения были сформированы из областей исходного объекта, содержащих модуляции контраста (одно изображение), ориентации (второе изображение) и пространственной частоты (третье изображение). Сами эти области предварительно выделялись из объекта с помощью разработанной модели фильтров второго порядка. В первом эксперименте за внимание конкурировали изображения, сформированные из модуляций разной размерности. Во втором – изображения одной размерности, отличающиеся по пространственной частоте. Привлечение внимания определялось путем регистрации движений глаз.
 Результаты. Обнаружено, что в конкуренции между размерностями преимущество имели модуляции контраста и ориентации. Когда выбор осуществлялся между изображениями одной размерности, побеждали изображения, сформированные из «средних» пространственных частот.
 Обсуждение результатов. Впервые получены данные о приоритетах среди модуляций в конкуренции за внимание. Установлено, что чем выше средний выход фильтров второго порядка, формирующих тестовое изображение, тем выше вероятность того, что это изображение привлечет внимание испытуемого.
 Заключение. Делается вывод, что фильтры второго порядка могут играть роль ворот внимания, при этом преимущество в конкуренции за внимание в задаче обнаружения получают фильтры с большей величиной сигнала на своем выходе. В приложении описываются модели зрительных механизмов второго порядка, использованные при подготовке стимульного материала.

Interhemispheric asymmetry of reactions to spatial modulations of local visual indications

Visual perception starts with a parallel spatial-frequency filtering. A visual scene is presented by a number of local indications in outputs of first-order filters. Their spatial association is the next important operation. It is the grouping of local indicators that underlies the transition to spatial vision. Recent research indicates that second-ordervisual filters perform this grouping. It is believed that the right hemisphere plays the leading role in spatial vision.The present study puts forward a hypothesis that this dominance can be formed even at the stage of the transition from a local to a global description of visual scenes. For this purpose the authors investigated interhemispheric asymmetry of potentials caused by functioning of second-order visual filters. These elements integrate the outputsof first-order filters and respond to spatial modulations of local visual indications. To solve this problem the authors recorded visual evoked potentials to a non-modulated texture and textures sinusoidally modulated in orientation, spatial frequency, and contrast. Next, they subtracted the response to the non-modulated texture from theresponse to the modulated texture. In result, each derivation received three different waves (d-waves): to the modulation of contrast, orientation, or spatial frequency. The comparison of d-waves in symmetric derivations revealed that its amplitude for all theused modulations is higher in the right hemisphere. Interhemispheric asymmetry to the modulation of orientation was most pronounced; it manifested itself better in occipital regions. The findings of the study showed the leading role of the right hemisphere in the processes of spatial association of local visual indications.

Models of Second-Order Visual Filters Selective to Modulation Dimension

Models of Second-Order Visual Filters Selective to Modulation Dimension

Quantitative tests-based assessment of biomedical image enhancement procedures

This paper describes a novel method of images enhancement procedures evaluation. A necessity of such method follows from the fact that the results of morphological or statistical image analysis in medical and/or technological applications strongly depend on the effectiveness of image preprocessing. The proposed method is based on standard images called testing sets composed of several basic patterns. Filtered testing sets are compared to basic patterns and the averaged distances between them are used as primary filtering quality scores. Then, they are used to calculation of several secondary parameters called image restoration errors. The image restoration errors make possible separate characterization of filters’ ability to improve image contrast, discrimination of small details or neglect the influence of image parallel shifts on the visibility of image details. Practical application of the proposed method is illustrated by example of comparison of the quality of three exemplary filters: a one based on second-level morphological spectra, Laplace and Sobel, filters. Similar comparison has been performed on the same filters combined with image binary thresholding procedures. At last, the numerical evaluation is compared to visual filters evaluation based on the results of NMR brain image enhancement reached by using different filtering methods.