Visual perception alterations in COVID-19:a preliminary study

AIM:To compare the visual perception(color and chromatic-achromatic contrast vision)of a small cohort of COVID-19 patients at the time of infection and after 6mo with that of a healthy population matched for sex and age.METHODS:A total of 25 patients(9 females,16 males,mean age:54±10y)with COVID-19 hospitalized in the COVID-19 Unit of the University Clinical Hospital of Valladolid were recruited for this preliminary study.Visual perception,as determined by monocular measurement of contrast sensitivity function(CSF)and color vision was assessed in each patient using the Optopad test.The results obtained were then compared with those of a sample of 16 age-and sex-matched healthy controls(5 females,11 males,mean age:50±6y)in which the same measurement procedure was repeated.Statistically significant differences between groups were assessed using the Mann-Whitney U test.Measurements were repeated after a minimum follow-up period of 6mo and statistically significant differences between the two time points in each group were assessed using the Wilcoxon signed rank test.RESULTS:Discrimination thresholds(color and chromatic-achromatic contrast vision)and their corresponding sensitivity,calculated as the inverse of the discrimination threshold,were evaluated.Analysis of the data revealed higher contrast threshold results(i.e.,worse contrast sensitivity)in the COVID-19 group than in the control group for all spatial frequencies studied in the Optopad-CSF achromatic test and most of the spatial frequencies studied in the Optopad-CSF chromatic test for the red-green and blue-yellow mechanisms.In addition,color threshold results in the COVID-19 group were also significantly higher(i.e.,worse color sensitivity)for almost all color mechanisms studied in the Optopad-Color test.At 6mo,most of the differences found between the groups were maintained despite COVID-19 recovery.CONCLUSION:The present results provide preliminary evidence that visual perception may be impaired in COVID-19,even when the infection has passed.Although further research is needed to determine the precise causes of this finding,analysis of CSF and color vision could provide valuable information on the visual impact of COVID-19.

Effect of visual perception training on binocular visual function reconstruction in patients after strabismus surgery

AIM:To explore the effect of visual perception learning software training(VPT)on binocular visual function reconstruction in children with intermittent exotropia after strabismus surgery.METHODS:Ninety children with intermittent exotropia admitted to our hospital from June 2018 to December 2018 were included,and randomly divided into VPT and control groups.Children in the control group received basic binocular vision training,while those in the VPT group received VPT after strabismus surgery.Tertiary visual function,visual perception function,Newcastle Control Score(NCS),and ocular position retraction rate were compared at 3 and 12mo after the surgery.RESULTS:At 3 and 12mo after the surgery,the proportion of simultaneous perception,binocular fusion version and binocular stereo vision in the VPT group was conspicuously higher than that in the control group(P<0.05).After the vision training,the binocular visual perception functions of children in both groups were significantly improved compared with that before training(P<0.05).Interestingly,the grating sharpness,texture perception and texture motion perception in the VPT group were dramatically better than control group(P<0.01).The NCS in the VPT group was significantly lower than that in the control group(P<0.05).The ocular position retraction rate in the VPT group was significantly lower than that in the control group at 12mo(8.89%vs 26.67%,P=0.03).CONCLUSION:VPT effectively promotes binocular visual function reconstruction in intermittent exotropia children after strabismus surgery and reduces the strabismus severity and ocular position retraction rate.

Photonic synapses with ultralow energy consumption for artificial visual perception and brain storage

The human visual system,dependent on retinal cells,can be regarded as a complex combination of optical system and nervous system.Artificial retinal system could mimic the sensing and processing function of human eyes.Optically stimulated synaptic devices could serve as the building blocks for artificial retinas and subsequent information transmission system to brain.Herein,photonic synaptic transistors based on polycrystalline MoS_(2),which could simulate human visual perception and brain storage,are presented.Moreover,the photodetection range from visible light to near-infrared light of MoS_(2) multilayer could extend human eyes’vision limitation to near-infrared light.Additionally,the photonic synaptic transistor shows an ultrafast speed within 5μs and ultralow power consumption under optical stimuli about 40 aJ,several orders of magnitude lower than biological synapses(50 ms and 10 fJ).Furthermore,the backgate control could act as emotional modulation of the artificial brain to enhance or suppress memory function,i.e.the intensity of photoresponse.The proposed carrier trapping/detrapping as the main working mechanism is presented for the device.In addition,synaptic functionalities including short synaptic plasticity,long synaptic plasticity and paired-pulse facilitation could be successfully simulated based on the prepared device.Furthermore,the large difference between short synaptic plasticity and long synaptic plasticity reveals the better image pre-processing function of the prepared photonic synapses.The classical Pavlovian conditioning associated with the associative learning is successfully implemented as well.Therefore,the efficient and rich functionalities demonstrate the potential of the MoS_(2) synaptic device that integrates sensing-memory-preprocessing capabilities for realizing artificial neural networks with different emotions that mimic human retina and brain.

MF-CFI:A fused evaluation index for camouflage patterns based on human visual perception

The evaluation index of camouflage patterns is important in the field of military application.It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism.In order to make the evaluation method more computationally intelligent,a Multi-Feature Camouflage Fused Index(MF-CFI)is proposed based on the comparison of grayscale,color and texture features between the target and the background.In order to verify the effectiveness of the proposed index,eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index(UIQI),Camouflage Similarity Index(CSI)and Structural Similarity(SSIM).Twenty-four different simulated targets are designed in a grassland background,28 observers participate in the experiment and record the eye movement data during the observation process.The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data,both in the designed digital camouflage patterns and largespot camouflage patterns.Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception,the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.

Achieving the Visual Perception and Gestalt Psychology in Sultan Hassan Mosque Building

The gestalt principles are perception and what is visually communicated by objects. These principles describe the visual language within which we work. Understanding how a designer realizes things visually will help designers communicate better. Many designers use Gestalt principles to have a structure visual stimulus, so as to create interfaces that are easy for users to understand. Because the understanding of visual perception is a critical item in any designer’s toolkit. Islamic heritage buildings also contain many architectural values, especially the Sultan Hassan Mosque in Cairo. Through this paper, we will verify the use of gestalt principles of visual perception in the building design. Because the psychological organization of the design, achieves the understanding and awareness of the current relationships between the elements, depending on the extent of regularity, accuracy, and consistency of the design elements. This makes us recognize the esthetic values of Sultan Hassan’s building and mosque. The visual delight we get from architecture begins with how we perceive it. So, in order to understand how visual delight arises, we must first understand how we perceive and interpret visual stimuli. Especially since the principles of gestalt confirm that the human brain tends to make tricks and illusions. Therefore, we found the mosque designer had exploited this fact during the design process, to exclude any possibility of the resulting misunderstanding. The designer achieved the psychological preparation of the visitor by using some principles of visual perception of the Gestalt theory, such as growth, continuity, and hierarchy.

Natural Scene Classification Inspired by Visual Perception and Cognition Mechanisms

The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural scenes.Inspired by this fact,we propose a biologically plausible approach for natural scene image classification.This approach consists of one visual perception model and two visual cognition models.The visual perception model,composed of two steps,is used to extract discriminative features from natural scene images.In the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure signals.In the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure signals.Then we design a cognitive feedback model to realize adaptive optimization for the visual perception model.At last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene categorization.Experiments on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.

Visual perception driven 3D building structure representa tion from airborne laser scanning point cloud

Background Three-dimensional(3D)building models with unambiguous roof plane geometry parameters,roof structure units,and linked topology provide essential data for many applications related to human activities in urban environments.The task of 3D reconstruction from point clouds is still in the development phase,especially the recognition and interpretation of roof topological structures.Methods This study proposes a novel visual perception-based approach to automatically decompose and reconstruct building point clouds into meaningful and simple parametric structures,while the associated mutual relationships between the roof plane geometry and roof structure units are expressed by a hierarchical topology tree.First,a roof plane extraction is performed by a multi-label graph cut energy optimization framework and a roof structure graph(RSG)model is then constructed to describe the roof topological geometry with common adjacency,symmetry,and convexity rules.Moreover,a progressive roof decomposition and refinement are performed,generating a hierarchical representation of the 3D roof structure models.Finally,a visual plane fitted residual or area constraint process is adopted to generate the RSG model with different levels of details.Results Two airborne laser scanning datasets with different point densities and roof styles were tested,and the performance evaluation metrics were obtained by International Society for Photogrammetry and Remote Sensing,achieving a correctness and accuracy of 97.7%and 0.29m,respectively.Conclusions The standardized assessment results demonstrate the effectiveness and robustness of the proposed approach,showing its ability to generate a variety of structural models,even with missing data.

The Color of Natural Teeth Investigated by Visual Perception and Spectrophotometer

The advantage of electronic devices is to eliminate the subjectivity. Based on individual capabilities, visual perception has its disadvantages. The aim of this study was to find out the possible shade difference between the upper and lower teeth, visual perception versus spectrophotometry as well as proving that females are better in visual perception of colour matching. 82 subjects (dental students) of this study determined the color of each other’s natural teeth. The color of 1640 teeth (incisors, canines and premolars), was matched by visual perception and by Vita Easyshade spectrophotometer. The matching was focused on the middle third of buccal surfaces of the examined teeth. In this study, it was found that there was a difference of color between the teeth of the upper and lower jaw. The percentage of the accordance between two methods was 28.35% for all examined teeth. The color determination at central incisors showed the highest value of accordance 40.85%. Based on Vitapan 3D Mastershade, the most frequent color was 2M2.

Assessing Linear Urban Landscape from dynamic visual perception based on urban morphology

As an essential part of the urban landscape,linear urban landscape(LUL)is the interaction between humans and nature,which is closely associated with daily life and brings multiple characteristics to visual perception.Current studies focus on complex models that describe visual perception using static viewpoints,but lossing the continuous and dynamic features of visual perception.This paper provides a general framework that can quantify dynamic visual perception based on urban morphology and improves accuracy in the descriptions of LUL linear spatial characteristics.Based on Beijing-Hangzhou Grand Canal(Hangzhou urban section),the proposed framework combines the indicators of multiple dimensions to quantify dynamic visual perception and emphasizes the continuity of LUL.To represent the dynamic visual perception and the spatial pattern characteristics of LUL,different evaluation criteria of indicators are set according to landscape scales.To minimize subjectivity and uncertainty caused by subjective cognition and fulfill the landscape pattern under different urban development policies,we set up distinct scenario preference patterns.With appropriate fine-tuning of scenario preference patterns and setting of movement types,the proposed method can be adapted to other LUL projects and aspires to provide a general methodology and scientific guidance for urban planning and landscape management.

Visual perception driven collage synthesis

A collage is a composite artwork made from the spatial layout of multiple pictures on a canvas,collected from the Internet or user photographs.Collages,usually made by skilled artists,involve a complex manual process,especially when searching for component pictures and adjusting their spatial layout to meet artistic requirements.In this paper,we present a visual perception driven method for automatically synthesizing visually pleasing collages.Unlike previous works,we focus on how to design a collage layout which not only provides easy access to the theme of the overall image,but also conforms to human visual perception.To achieve this goal,we formulate the generation of collages as a mapping problem:given a canvas image,first,compute a saliency map for it and a vector field for each sub-region of it.Second,using a divide-and-conquer strategy,generate a series of patch sets from the canvas image,where the salient map and the vector field are used to determine each patch’s size and direction respectively.Third,construct a Gestalt-based energy function to choose the most visually pleasing and orderly patch set as the final layout.Finally,using a semantic-color metric,map the picture set to the patch set to generate the final collage.Extensive experimental and user study results show that this method can generate visual pleasing collages.

Research on the Perception of Green Visual Exposure Space Based on SD Method:Taking Saishang Old Street Cultural Area in Hohhot as an Example

With the rapid development and improvement of urban construction,the influence of green environmental exposure on mental health has attracted increasing attention,but the relationship between the psychological perception and the object index has been less explored.From the perspective of the individual and environmental perception,space optimization of cultural blocks was discussed to provide a reference for the development of other old streets.

Application of Eye Movement Analysis in Landscape Visual Quality Evaluation

The existing methods of landscape visual quality evaluation is mostly based on people's subjective feelings,and the objectivity and scientificity of evaluation results are insufficient.As an important means of experimental psychology,eye movement technology can show great advantages and potential in landscape visual quality evaluation.On the basis of combing and summarizing the relevant literature,based on the explanation of the technical principle of eye movement analysis,the application field,research content,technical methods and other aspects of eye movement analysis were reviewed.The application prospect of eye movement technology in landscape visual quality evaluation was explored to provide theoretical reference for the in-depth evaluation and research of landscape visual quality evaluation theory.

Landscape Aesthetic Foundation Based on the Theory of Visual Perceptual Dynamics

With the acceleration of urban renewal,people’s demand for improving the overall urban landscape quality of the city is increasing.However,it is often found in project practice that some professionals have one-sided understanding or misunderstanding of landscape,which directly affects the work effi ciency of landscape design and the landscape quality of design works.Based on the theory of visual perceptual dynamics,this paper explores the aesthetic basis of people’s viewing and evaluation of visual objects from the aspects of viewpoint state,visual direction state and visual impressions formed in the mind,and excavates the true connotation of landscape.The research results show that there is no socalled landscape without viewpoint.The landscape is a visual perception process in which people experience the landscape of object at the appropriate viewpoint,not just the beauty of structure and form of the object.People’s impression of landscape is mainly determined by whether the object’s viewpoint fi eld can make aesthetic subject see easily,whether there is any barrier in the direction of view,whether the size is appropriate in scale,and whether the visual impression gives people a sense of peace of mind and comfort.

Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark visibility.An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation.Then,a visual perception factor computation model is devised by fusing texture and luminance characteristics.An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain.Moreover,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal.The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding.Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.

An Edge Visual Incremental Perception Framework Based on Deep Semi-supervised Learning for Monitoring Power Transmission Lines

In recent years,several efforts have been made to develop power transmission line abnormal target detection models based on edge devices.Typically,updates to these models rely on participation of the cloud,which means that network resource shortages can lead to update failures,followed by unsatisfactory recognition and detection performance in practical use.To address this problem,this article proposes an edge visual incremental perception framework,based on deep semisupervised learning,for monitoring power transmission lines.After generation of the initial model using a small amount of labeled data,models trained using this framework can update themselves based on unlabeled data.A teacher-student joint training strategy,a data augmentation strategy,and a model updating strategy are also designed and adopted to improve the performance of the models trained with this framework.The proposed framework is then examined with various transmission line datasets with 1%,2%,5%,and 10%labeled data.General performance enhancement is thus confirmed against traditional supervised learning strategies.With the 10%labeled data training set,the recognition accuracy of the model is improved to exceed 80%,meeting the practical needs of power system operation,and thus clearly validating the effectiveness of the framework.

Recent progress in optoelectronic neuromorphic devices

Rapid developments in artificial intelligence trigger demands for perception and learning of external environments through visual perception systems.Neuromorphic devices and integrated system with photosensing and response functions can be constructed to mimic complex biological visual sensing behaviors.Here,recent progresses on optoelectronic neuromorphic memristors and optoelectronic neuromorphic transistors are briefly reviewed.A variety of visual synaptic functions stimulated on optoelectronic neuromorphic devices are discussed,including light-triggered short-term plasticities,long-term plasticities,and neural facilitation.These optoelectronic neuromorphic devices can also mimic human visual perception,information processing,and cognition.The optoelectronic neuromorphic devices that simulate biological visual perception functions will have potential application prospects in areas such as bionic neurological optoelectronic systems and intelligent robots.

Image Dehazing Based on Pixel Guided CNN with PAM via Graph Cut

Image dehazing is still an open research topic that has been undergoing a lot of development,especially with the renewed interest in machine learning-based methods.A major challenge of the existing dehazing methods is the estimation of transmittance,which is the key element of haze-affected imaging models.Conventional methods are based on a set of assumptions that reduce the solution search space.However,the multiplication of these assumptions tends to restrict the solutions to particular cases that cannot account for the reality of the observed image.In this paper we reduce the number of simplified hypotheses in order to attain a more plausible and realistic solution by exploiting a priori knowledge of the ground truth in the proposed method.The proposed method relies on pixel information between the ground truth and haze image to reduce these assumptions.This is achieved by using ground truth and haze image to find the geometric-pixel information through a guided Convolution Neural Networks(CNNs)with a Parallax Attention Mechanism(PAM).It uses the differential pixel-based variance in order to estimate transmittance.The pixel variance uses local and global patches between the assumed ground truth and haze image to refine the transmission map.The transmission map is also improved based on improved Markov random field(MRF)energy functions.We used different images to test the proposed algorithm.The entropy value of the proposed method was 7.43 and 7.39,a percent increase of4.35%and5.42%,respectively,compared to the best existing results.The increment is similar in other performance quality metrics and this validate its superiority compared to other existing methods in terms of key image quality evaluation metrics.The proposed approach’s drawback,an over-reliance on real ground truth images,is also investigated.The proposed method show more details hence yields better images than those from the existing state-of-the-art-methods.

Perceptual Visuo-Motor Skills and Handwriting Production of Children With Learning Disabilities

This study aimed to explore the performance of the perceptual-visuomotor skills and the production of handwriting in children with Learning Disabilities.A total of 56 children participated,being a convenience sample,of both sexes,average age of eight years old,from 3rd to 5th grade level of Elementary School.The children were divided into the following groups:GI(28 children diagnosed with Learning Disabilities);GII(28 children with good academic performance,paired with GI in relation to chronological age and sex).They were evaluated individually in dysgraphic scale,visual perception development test,and fine motor evaluation.Data analysis was performed.There was a significant difference between GI and GII for the subtests of eye-hand coordination,copying,visual closure,fine motor precision,and fine manual control tests.They had difference between the groups for handwriting performance in descending and/or ascending subtests,irregularity of dimension,poor forms,and total score of Dysgraphia Scale.The results presented in this study indicate that children with Learning Disabilities can manifest significant visomotor impairment and deficit in legibility and handwriting quality,causing failures in the elaboration of sensorimotor plans that,added to the intrinsic deficit of long-term memory,result in persistent academic difficulties.

Effects of visual restoration on gait performance and kinematics of lower extremities in patients with age-related cataract

Background:Visual inputs are critical for locomotor navigation and sensorimotor integration in the elderly;however,the mechanism needs to be explored intensively.The present study assessed the gait pattern after cataract surgery to investigate the effects of visual restoration on locomotion.Methods:The prospective study recruited 32 patients(70.1±5.2 years)with bilateral age-related cataracts in the Department of Ophthalmology at Peking University Third Hospital from October 2016 to December 2019.The temporal-spatial gait parameters and kinematic parameters were measured by the Footscan system and inertial measurement units.Paired t-test was employed to compare data normally distributed and Wilcoxon rank-sum test for non-normally distributed.Results:After visual restoration,the walking speed increased by 9.3%(1.19±0.40 m/s vs.1.09±0.34 m/s,P=0.008)and exhibited an efficient gait pattern with significant decrease in gait cycle(1.02±0.08 s vs.1.04±0.07 s,P=0.012),stance time(0.66±0.06 s vs.0.68±0.06 s,P=0.045),and single support time(0.36±0.03 s vs.0.37±0.02 s,P=0.011).High amplitude of joint motion was detected in the sagittal plane in the left hip(37.6°±5.3°vs.35.5°±6.2°,P=0.014),left thigh(38.0°±5.2°vs.36.4°±5.8°,P=0.026),left shank(71.9°±5.7°vs.70.1°±5.6°,P=0.031),and right knee(59.1°±4.8°vs.56.4°±4.8°,P=0.001).The motor symmetry of thigh improved from 8.35±5.30%to 6.30±4.73%(P=0.042).Conclusions:The accelerated gait in response to visual restoration is characterized by decreased stance time and increased range of joint motion.Training programs for improving muscle strength of lower extremities might be helpful to facilitate the adaptation to these changes in gait.

Overview of 3D Scene Viewpoints evaluation method

The research on 3D scene viewpoints has been a frontier problem in computer graphics and virtual reality technology.In a pioneering study,it had been extensively used in virtual scene understanding,image-based modeling,and visualization computing.With the development of computer graphics and the human-computer interaction,the viewpoint evaluation becomes more significant for the comprehensive understanding of complex scenes.The high-quality viewpoints could navigate observers to the region of interest,help subjects to seek the hidden relations of hierarchical structure,and improve the efficiency of virtual exploration.These studies later contributed to research such as robot vision,dynamic scene planning,virtual driving and artificial intelligence navigation.The introduction of visual perception had The introduction of visual perception had contributed to the inspiration of viewpoints research,and the combination with machine learning made significant progress in the viewpoints selection.The viewpoints research also has been significant in the optimization of global lighting,visualization calculation,3D supervising rendering,and reconstruction of a virtual scene.Additionally,it has a huge potential in novel fields such as 3D model retrieval,virtual tactile analysis,human visual perception research,salient point calculation,ray tracing optimization,molecular visualization,and intelligent scene computing.