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.

A PERSONALIZED IMAGE RETRIEVAL BASED ON VISUAL PERCEPTION

A new scheme named personalized image retrieval technique based on visual perception is proposed in this letter, whose motive is to narrow the semantic gap by directly perceiving user's visual information. It uses visual attention model to segment image regions and eye-tracking technique to record fixations. Visual perception is obtained by analyzing the fixations in regions to measure gaze interests. Integrating visual perception into attention model is to detect the Regions Of Interest (ROIs), whose features are extracted and analyzed, then feedback interests to optimize the results and construct user profiles.

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.

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 on the architectural elements of the built heritage of a historic temple town： A case study of Kumbakonam, India

This paper aims to investigate the changes in the virtual perception on the built heritage at the traditional core setttement of Kumbakonam Town at Tamitnadu and to analyze their implica- tions. Specifically, the major objectives of the study are （1） to identify the architectural elements that manifest the built heritage of Kumbakonam Town and （2） to assess the contMbutions of these elements to the changes in the visuat perception of the town. To achieve these objectives, this study adopts an empirical model that analyzes the architectural elements of the buildings in the study area. Direct observations and documentations of 373 buildings are collected to analyze those etements that contribute to the changes in the visual perception on the built heritage of Kumbakonam Town. An ordinary regression model is used to examine the characteristics of the built heritage across the chariot processional route of the town. Several architectural elements, including pitasters, horizontal cornices, arched windows, and ornamental parapets, improve the image of the town. These empirical findings support the policy framework that enhances the visual perception of Kumbakonam Town.

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.

Connecting Language with Perception and Action for Human-robot Interaction

To build robots that engage in intuitive communication with people by natural language, we are developing a new knowledge representation called conceptual network model. The conceptual network connects natural language concepts with visual perception including color perception, shape perception, size perception, and spatial perception. In the implementation of spatial perception, we present a computational model based on spatial template theory to interpret qualitative spatial expressions. Based on the conceptual network model, our mobile robot can understand user's instructions and recognize the object referred to by the user and perform appropriate action. Experimental results show our approach promising.

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.

Recent Advances and Challenges of Visual Signal Quality Assessment

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.

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.