Characteristics Of Visual Perception Research Articles

Feature-level contrastive learning for full-reference light field image quality assessment

Light field (LF), as a new visual information representation for immersive experiences in virtual reality and augmented reality, has attracted extensive attention. It is of significance to establish the light field image quality assessment (LF-IQA) that conforms to the characteristics of human visual perception. Due to the spatial–angular inter-twined imaging mechanism, the quality evaluation for LF images faces more challenges than ordinary 2D/3D IQA. This paper proposes a feature-level contrastive learning based full-reference LF-IQA with a divide-and-conquer learning strategy. It first employs the cross-attention mechanism to learn the local contrast features related to the reference features from three subsets of distorted sub-aperture images (SAIs). Then a Transformer-based feature fusion is used to predict the overall perceptual quality. The evaluation experiments are carried out on three commonly used LF-IQA datasets: Win5-LID, NBU-LF1.0, and SHU. The experimental results demonstrate that our model outperforms the existing state-of-the-art LF-IQA methods.

Stimulus-dependent differences in cortical versus subcortical contributions to visual detection in mice

The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with the V1 supporting the perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports the perception of many of the same visual features traditionally associated with the V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to the detection of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near their perceptual threshold while white noise patterns of optogenetic stimulation were delivered to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in the SC are critical for the detection of both luminance and contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK but no sign of a comparable modulation for luminance detection. The data suggest that behavioral detection of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both the SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually guided behaviors.

A modified atmospheric scattering model and degradation image clarification algorithm for haze environments

Addressing the limitation of existing image dehazing algorithms based on atmospheric scattering models, which often overlook the underlying physical causes of color distortion in hazy images, resulting in suboptimal algorithm robustness and image clarity when faced with varying levels of haze pollution, this study introduces a refined atmospheric scattering model. It also presents a haze image clarity algorithm based on this modified atmospheric scattering model by analyzing the fundamental factors contributing to image degradation and distortion caused by haze. Initially, the hazy image undergoes conversion to a new HSI color space. The hazy image is aligned more closely with human visual perception characteristics by implementing an adaptive saturation enhancement technique and adjusting contribution coefficients for the three RGB channels to the luminance component. Subsequently, the hazy image is partitioned into dense haze and non-dense haze regions based on haze distribution characteristics within the image. A global light intensity computation method is devised for the hazy image utilizing a quad-tree segmentation algorithm. Following this, calculations are performed to determine the atmospheric light value and transmittance for dense and non-dense haze regions separately. The global atmospheric light and transmittance values are then derived based on the probability density function of the dense haze region using Alpha Fusion. Finally, corrections are applied to the global atmospheric light values using an atmospheric light correction vector, while denoising the global transmittance is achieved through a fast non-local mean filtering algorithm. Experimental findings demonstrate that the proposed haze image clarity algorithm, grounded in the modified atmospheric scattering model, exhibits adaptability across various degrees and types of haze images. Comparative analysis against other prominent image dehazing algorithms reveals its efficacy in addressing severe color distortion in dense haze scenarios, achieving a more natural clarity effect, and showcasing superior performance across all numerical evaluation metrics.

Characteristics of visual perception of patients’ faces and the formation of “observation” in the process of training cosmetologists

Professional experience assists specialists in processing information more quickly and effectively making precise decisions. Visual expertise, as a crucial component of experience, refers to the capability to rapidly perceive visual information within a specific professional domain, acquired through systematic education, professional development, and practice. Numerous studies utilize eye-tracking methods to analyze the relationship between professional experience and gaze patterns. For instance, experienced dermatologists have developed optimal scanning patterns, allowing them to efficiently allocate attention and accurately identify key diagnostic features within images amidst numerous secondary details. The purpose of this study is to analyze changes in oculomotor patterns after completing the author’s training program for doctors, aimed at versatile aesthetic analytics of the face, building individual treatment protocols and increasing the patient’s adherence to aesthetic medicine in order to assess the possibility of developing observation in the conditions of short-term training. Thirty cosmetic doctors participated in the study, which utilized eye-tracking methods with the Neuroburo program-hardware complex. The study was conducted in two phases – before and after training – with 15 patient facial images exhibiting various dermatological issues presented on a computer screen to the cosmetic doctors. Participants were tasked with identifying signs of dermatological disorders of the patients. Following training, a decrease in the number of fixations, an increase in saccadic amplitude, and a reduction in the overall scanning path length were observed among the cosmetic doctors. These findings indicate a more optimized perception strategy and suggest a more systematic and directed approach to diagnostic image analysis. The results suggest an enhanced global perception ability among the doctors, which may aid in recognizing broader patterns and structures and understanding the wider context and relationships between details.

Spatial Intelligent Design and Innovation for Indoor Environment - Visualization and Analysis of Web3D Technology

Abstract Along with the popularization and expanding influence of Internet applications, Web 3D is born from various mature technologies driven by the demand for commercial interests in the Internet. This study designs an interactive intelligent design method for indoor environment space based on Web 3D, which has cross-platform and high-performance graphic drawing capability and covers indoor lighting material transformation, smooth switching of viewpoints, zooming of areas, and other interactive modes. It has cross-platform and high-performance graphic drawing capabilities and covers indoor lighting material change, smooth switching of viewpoints, area zoom, and other features. Based on the visual perception characteristics of the human eye, we obtain the user’s most realistic experience of the color of the indoor space and then construct the virtual indoor environmental space through the Web 3D system, and carry out a visual analysis of the indoor space under different materials and colors. The results show that under the visual analysis of Web 3D, the optimal distribution of color luminance values affecting the visual psychology of indoor environmental space is between 30.5 and 68.9nit, with a mean value of 49.59nit. The results can establish a favorable basis for the later indoor color configuration, which is in line with the visual characteristics of the human eye in indoor color configuration design practice.

Graph-Represented Distribution Similarity Index for Full-Reference Image Quality Assessment.

In this paper, we propose a graph-represented image distribution similarity (GRIDS) index for full-reference (FR) image quality assessment (IQA), which can measure the perceptual distance between distorted and reference images by assessing the disparities between their distribution patterns under a graph-based representation. First, we transform the input image into a graph-based representation, which is proven to be a versatile and effective choice for capturing visual perception features. This is achieved through the automatic generation of a vision graph from the given image content, leading to holistic perceptual associations for irregular image regions. Second, to reflect the perceived image distribution, we decompose the undirected graph into cliques and then calculate the product of the potential functions for the cliques to obtain the joint probability distribution of the undirected graph. Finally, we compare the distances between the graph feature distributions of the distorted and reference images at different stages; thus, we combine the distortion distribution measurements derived from different graph model depths to determine the perceived quality of the distorted images. The empirical results obtained from an extensive array of experiments underscore the competitive nature of our proposed method, which achieves performance on par with that of the state-of-the-art methods, demonstrating its exceptional predictive accuracy and ability to maintain consistent and monotonic behaviour in image quality prediction tasks. The source code is publicly available at the following website https://github.com/Land5cape/GRIDS.

Features of visual perception of the historical environment of the Desyatynna Church in Kyiv

Landscape, especially urban landscape, contributes to the formation of a sense of place. The identification of the perception characteristics of the historical image of Kyiv city, based on visual landscape research, was conducted with the aim of establishing visual connections and areas between sacred structures in the complex relief conditions of the Starokyivska Hill. The study applied methods for determining the quantitative indicators of spatial-visual characteristics of the studied locality based on a planned route survey. The parameters of the main selected points were determined by depth of visibility, horizontal viewing angle, presence of focal points, accents, types of perspectives, and types of space. Through visual landscape research, the dynamics of visual connections and areas between elements in the historical landscape of Kyiv were identified. The absence of changes in the spatial-visual characteristics was established at three selected points, while changes were found in others. Specifically, the changes are characterized by a decrease in the depth of visibility along the visual axis between the Desyatynna Church and the St. Andrew’s Church. The need to search for ways to model the outline of the landscape in the complex relief conditions of the Starokyivska Hill is revealed for the perspective of preserving the historical image and improving spatial solutions in the urban environment.

OMOFuse: An Optimized Dual-Attention Mechanism Model for Infrared and Visible Image Fusion

Infrared and visible image fusion aims to fuse the thermal information of infrared images and the texture information of visible images into images that are more in compliance with people’s visual perception characteristics. However, in the existing related work, the fused images have incomplete contextual information and poor fusion results. This paper presents a new image fusion algorithm—OMOFuse. At first, both the channel and spatial attention mechanisms are optimized by a DCA (dual-channel attention) mechanism and an ESA (enhanced spatial attention) mechanism. Then, an ODAM (optimized dual-attention mechanism) module is constructed to further improve the integration effect. Moreover, a MO module is used to improve the network’s feature extraction capability for contextual information. Finally, there is the loss function ℒ from the three parts of SSL (structural similarity loss), PL (perceptual loss), and GL (gap loss). Extensive experiments on three major datasets are performed to demonstrate that OMOFuse outperforms the existing image fusion methods in terms of quantitative determination, qualitative detection, and superior generalization capabilities. Further evidence of the effectiveness of our algorithm in this study are provided.

Representation of a Perceptual Event in an Interview with an Artist

Introduction. The purpose of the research is to consider the linguistic actualization of the main characteristics of the artist's visual perception in the interview discourse. The relevance of the research is due to its inclusion in the context of modern anthropo-oriented study of cognition of the world by a creative person. The novelty of the research lies in the fact that for the first time the process of perception of the world by an English-speaking artist is studied as an event within the framework of a complex linguistic and cognitive approach, which allows to analyze its specificity to the fullest extent.Methodology and sources. The methodological basis of the research was made up of the works of the linguists-cognitologists L.V. Laenko, I.Yu. Kolesov, psychologist V. A. Barabanshchikov who revealed distinctive characteristics of perceptual image and substantiated the expediency of perception as an event. The research material was interviews with English-speaking artists from the Internet versions of the newspapers devoted to the life and work of modern artists. The methods of lexico-semantic, frame, contextual and pragmalinguistic analysis were used.Results and discussion. The article reveals the peculiarities of visual perception of the world by contemporary English-speaking artists, which are reflected in the discourse of the interview. The author reveals the multidimensionality of a subject of perception, different ways of its representation on the verbal level: as an observer-actor and as a “offscreen” observer. The paper shows the specificity of visual perception of the world by the artist as a perceptual event that possesses spatial and temporal coordinates and such significant characteristics as dynamism, motivation, focus and emotionality. The denotative situation of perception is actualized in English by personal pronouns, active-action predicates, perceptual predicates, existential constructions, phase verbs, and state change predicates. The important feature of the artist's creative perception of the world is the forming of the necessity of representation in his consciousness perceptive image by means of painterly signs. As a result of such representation the given perceptive image receives the further development and becomes the basis for creating an artistic image to be embodied in an art work.Conclusion. In the interview with the artist there is a complex process of cognition of the world by the creative person, based on the perceptual event. Visual perception is represented by the artist as a directed activity, which is to learn and which requires certain efforts and motivation. As a result of the perceptual event that the artist experiences, an artistic image is formed that is actualized in the work of art.

A Remote Sensing Image Quality Interpretation Scale Characterization Method Based on the TTP Criterion

Accurate grading of remote sensing image interpretation is crucial for improving image classification and screening efficiency. Through extensive research, the General Image Quality Equation (GIQE) based on the National Imagery Interpretability Rating Scale (NIIRS) has been developed. However, poor reliability and low accuracy issues remain due to the failure to consider human visual characteristics. This paper introduces the Target Task Performance (TTP) criterion as a key parameter to reflect the cascading degradation factors of human visual perception characteristics and system imaging links, which improves the reliability of the model. A New Optimized Remote Sensing Image Quality Equation (NORSIQE), which effectively predicted the interpretability of image information, is constructed. Using 200 sets of test data, the quantitative relationship between key parameters (GSD, TTP, and SNR) of the NORSIQE and the subjective NIIRS level is obtained by a least squares regression fit, and the determination coefficient of the model is as high as 0.916. The model is evaluated for accuracy using 120 sets of validation data, showing an 87% improvement compared to the GIQE4. This method provides theoretical support for the development of new methods for remote sensing image quality evaluation and the design of payloads for remote sensing imaging systems.

Application of Gestalt Psychology Principle in Decorative Film

This paper takes the principle of Gestalt psychology and decorative film as the research object, through analyzing the practical needs of decorative film pattern design, and discusses the principle of Gestalt psychology, similar principle, similar principle, closed principle, continuous principle, subject and background relationship, symmetry principle, etc., analyzes the application design of Gestalt psychology principle in decorative film pattern. Therefore, to get the physiological and psychological characteristics of visual perception is the only way to design patterns that conform to the law of human cognition.

Influencing factors of modern and contemporary decorative pattern design on users’ visual perception characteristics

Abstract There are many classic traditional arts incorporated in modern design patterns design. These traditional arts embody China’s profound national art in modern decorative patterns, making the organic combination of modern and traditional national art, thus realizing the promotion of traditional national art and providing more classical excellent elements for the development of modern decorative art. At the same time, modern decorative pattern design draws on traditional art from five aspects: composition, perspective, image, color, and allegory, and applies its advantages and strengths completely to the modern design process. The most important thing is that modern pattern design has a strong sensory impact on people’s visual perception. Therefore, modern decorative pattern design cannot be separated from the integration of traditional ethnic groups, and even more so from the inspiration and reference brought to it by traditional art. The article analyzes the dynamic changes of higher-order aberrations over time in the near-eye and ortho-eye groups from a design perspective by using the generalized additive mixture models (GAMMs). The threshold effect analysis is used to find the turning point of the dynamic change of higher-order aberration. The interaction analysis method compares the differences in the dynamic changes of higher-order aberrations between the two groups, analyzes the application of modern design to decorative patterns, combines ancient and modern design elements, and studies the impact of the combined product on human senses.

Perception of Visual Images in the Psychology of Art

The article presents a theoretical analysis of the phenomenology of visual perception in the psychology of fine art. Aspects of perception as one of the mental functions and visual images as meaningful perceptual phenomena are analyzed. The question of the predestination of perception, its development and foundations is discussed. With the help of the analysis of many fundamental sources, the main characteristic of visual perception, influence on modern culture and human thinking has been established. The possibilities of applying the psychology of art in psychological counseling are described. The practical methods of fine art are explained from the standpoint of psychology, as well as examples of the perception of visual images in art therapy based on the research of domestic and foreign authors are indicated. In conclusion, examples of human perception of visual images in psychodiagnostic techniques are considered, and prospects for future theoretical and practical work in the field of psychotherapy through the prism of fine art are outlined.

Feature-based attention warps the perception of visual features

Selective attention improves sensory processing of relevant information but can also impact the quality of perception. For example, attention increases visual discrimination performance and at the same time boosts apparent stimulus contrast of attended relative to unattended stimuli. Can attention also lead to perceptual distortions of visual representations? Optimal tuning accounts of attention suggest that processing is biased towards “off-tuned” features to maximize the signal-to-noise ratio in favor of the target, especially when targets and distractors are confusable. Here, we tested whether such tuning gives rise to phenomenological changes of visual features. We instructed participants to select a color among other colors in a visual search display and subsequently asked them to judge the appearance of the target color in a 2-alternative forced choice task. Participants consistently judged the target color to appear more dissimilar from the distractor color in feature space. Critically, the magnitude of these perceptual biases varied systematically with the similarity between target and distractor colors during search, indicating that attentional tuning quickly adapts to current task demands. In control experiments we rule out possible non-attentional explanations such as color contrast or memory effects. Overall, our results demonstrate that selective attention warps the representational geometry of color space, resulting in profound perceptual changes across large swaths of feature space. Broadly, these results indicate that efficient attentional selection can come at a perceptual cost by distorting our sensory experience.

The ability to interpret social signs by individuals with intellectual disturbance

The article is devoted to the specifics of adaptive navigation of individuals with intellectual impairments in the social environment. Characteristics of the cognitive sphere of intellectually impaired affect the perception and interpretation of public signs. The subject of the study is social navigation sign decoding. The object of the study is the ability to interpret social signs of young adolescents with intellectual impairments. The author considers such aspects as a social adaptation of persons with disabilities, navigation aids for people with special needs, features of visual perception of graphic images as elements of the public space sign environment of people with intellectual impairments. The main conclusion of the study is the confirmation of a lower ability of students with intellectual disabilities to decode public signs correctly compared with the control group. The general relevance of the navigation signs comprehension is highlighted, which is because of the studying the graphic navigation rules as a part of the educational process. The author's special contribution to the research field is the empirical validation of the fact that the combination of complex sign elements has a negative effect on the decoding of informative stimuli for orientation in the social environment. Effective sign navigation is conditioned by commonly accepted standards and considers cognitive limitations of persons with intellectual disturbances.

Blind Video Quality Assessment for Ultra-High-Definition Video Based on Super-Resolution and Deep Reinforcement Learning.

Ultra-high-definition (UHD) video has brought new challenges to objective video quality assessment (VQA) due to its high resolution and high frame rate. Most existing VQA methods are designed for non-UHD videos-when they are employed to deal with UHD videos, the processing speed will be slow and the global spatial features cannot be fully extracted. In addition, these VQA methods usually segment the video into multiple segments, predict the quality score of each segment, and then average the quality score of each segment to obtain the quality score of the whole video. This breaks the temporal correlation of the video sequences and is inconsistent with the characteristics of human visual perception. In this paper, we present a no-reference VQA method, aiming to effectively and efficiently predict quality scores for UHD videos. First, we construct a spatial distortion feature network based on a super-resolution model (SR-SDFNet), which can quickly extract the global spatial distortion features of UHD videos. Then, to aggregate the spatial distortion features of each UHD frame, we propose a time fusion network based on a reinforcement learning model (RL-TFNet), in which the actor network continuously combines multiple frame features extracted by SR-SDFNet and outputs an action to adjust the current quality score to approximate the subjective score, and the critic network outputs action values to optimize the quality perception of the actor network. Finally, we conduct large-scale experiments on UHD VQA databases and the results reveal that, compared to other state-of-the-art VQA methods, our method achieves competitive quality prediction performance with a shorter runtime and fewer model parameters.

RETRACTED: A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation

Unit charts are a common type of chart for visualizing scientific data. A unit chart is a chart used to communicate quantities of things by making the number of symbols on the chart proportional to the number of items represented. An accurate perception of the order of magnitude is essential to evaluating whether a unit chart can effectively convey information. Previous studies have primarily focused on perceptual properties at small order-of-magnitude scales or the efficacy of pictographs in unit charts. However, few researchers have explored the perceptual effectiveness of unit charts when representing large orders of magnitude. In this study, we performed a series of sampling measurements to investigate the visual–perceptual characteristics of unit charts when representing asymmetric interactions such as large-scale numbers. The results showed that under the restriction of the current conventional display medium, unit charts still offer a significant advantage over bar charts in a single-scale visual overview. However, this comes at the cost of a longer response time. Although this study constitutes basic research, accumulating evidence about how people reason about magnitudes beyond human perception is critical to the field of information science. This study may contribute to understanding how viewers perceive unit charts and the factors that influence graphical perception. This article provides some specific guidelines for designing unit charts that may be useful to visualization designers.

Features of the visual perception process: lexicographic aspect

This paper delves into the phenomenon of perception and the importance of analyzing a person’s interaction with the world. The study focuses on the visual perception as the primary channel for obtaining information. The objective is to identify the characteristics of visual perception, as verbalized through lexical and phraseological units in the Russian language. The researcher has analyzed 118 lexical and phraseological units that nominate visual perception. By examining dictionary entries of perceptual verbs and phraseological units, she has formed synonymous rows that share a common concretizing seme, which names the features of the process of visual perception. Certain verbs are included in multiple synonymous rows, their polysemy result in the actualization of several features. This can cause the boundaries within the field to become blurred. The core position is characterized by the feature of purposefulness, which refers to the subject’s orientation towards the object of perception. The closest feature to the core is effectiveness, which signifies the end of the process with a positive or negative result. Duration is associated with effectiveness and implies fixation on the object of perception for a certain period. The next feature is assessment, which expresses the subject’s attitude towards the object. Finally, on the periphery, there is unreality of visual perception, where the image is based on existing experience rather than the real object. This language model effectively represents the features of visual perception, making it accessible, informative, and complete.

Quality Feature Learning via Multi-Channel CNN and GRU for No-Reference Video Quality Assessment

Nowadays, video quality assessment (VQA) plays a vital role in video-related industries to predict human perceived video quality to maintain the quality of service. Although many deep neural network-based VQA methods have been proposed, the robustness and performance are limited by small scale of available human-label data. Recently, some transfer learning-based methods and pre-trained models in other domains have been adopted in VQA to compensate for the lack of enormous training samples. However, they result in a domain gap between the source and target domains, which provides sub-optimal feature representation for VQA tasks and deteriorates the accuracy. Therefore, in the paper, we propose quality feature learning via a multi-channel convolutional neural network (CNN) with a gated recurrent unit (GRU), taking into account both the motion-aware information and human visual perception (HVP) characteristics to solve the above issue for no-reference VQA. First, inspired by self-supervised learning (SSL), the multi-channel CNN is pre-trained on the image quality assessment (IQA) domain without using human annotation labels. Then, semi-supervised learning is applied on top of the pre-trained multi-channel CNN to fine-tune the model to transfer the domain from IQA to VQA while considering motion-aware information for better frame-level quality feature representation. After that, several HVP features are extracted with frame-level quality feature representation as the input of the GRU model to obtain the final precise predicted video quality. Finally, the experimental results demonstrate the robustness and validity of our model, which is superior to the state-of-the-art approaches and is closely related to human perception.

Light in the contemporary churches of the Ukrainian diaspora

Nowadays, the Ukrainian church building has not yet succeeded in establishing its own modern image/type of church, different from the conventional one. One of the significant reasons for this situation is the long break in the design and construction of churches in Ukraine during the 20th century. The Ukrainian diaspora has accumulated considerable experience in the construction of modern churches, which ensures the continuity of the tradition of the church building. The purpose of the research is to explore the still invaluable experience of designing church buildings and the architectural and artistic organisation of their interior in Ukrainian diaspora churches, which is an important foundation for solving the problem of developing the image/appearance of a modern church. The research used general scientific and special methods. Attention is devoted to the research of current issues of developing a light composition in the sacred space of modern diaspora churches. The research analyses several projects by architects of the Ukrainian diaspora in the field of sacred architecture. The research identifies the specific features of the establishment and development of church architecture in the Ukrainian diaspora in terms of the debate over the conventional and modern forms of church buildings and the spatial organisation of the light composition of their sacred space. The research outlines the influence of the local architectural tradition of the church building in North America – Protestant and Catholic churches – and the modernist design culture of the period of functionalism and neo-modernism in architecture on the architectonics of Ukrainian churches in the diaspora and the organisation of the light environment of their interior space. For the first time, the features and regularities of the organisation of the light environment of the most famous Greek Catholic churches of the Ukrainian diaspora in Canada and the United States, built in the second half of the 20th century, are explored. The influence of natural light on the architectonics of churches and the specific features of visual perception of their internal object environment and on the development of the appropriate mood imbued with mysticism and sacred atmosphere of the interiors of churches is determined. The experience of diaspora architects is explored and analysed, which has not been understudied but will be essential for use in the practice of Ukrainian architects in designing modern churches while preserving national identity and church-building traditions