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.

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.

Dynamic Visual Image Modeling Based on Mobile RobotSelf- Organizing Network in Internetof Things Perception Layer

The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.

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.

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.

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.

A GENERALIZED GOODNESS CRITERION FOR UNSUPERVISED NEURAL LEARNING OF VISUAL PERCEPTION

Unsupervised learning plays an important role in the neural networks. Focusing on the unsupervised mechanism of neural networks, a novel generalized goodness criterion for the unsupervised neural learning of visual perception based on the martingale measure is proposed in the paper. The differential geometrical structure is used as the framework of the whole inference and spatial statistical description with adaptive attribute is embedded in the corresponding nonlinear functional space. Consequently the integration of optimization process and computational simulation with the NeoDarwinian paradigm is obtained. And the generalization of the guidance for the evolutionary learning in the neural net framework, the convergence of the goodness and process of the evolution guaranteed by the mathematical features are discussed. This criterion has generic significance in the field of machine vision and visual pattern classification.

Visual Attributes of Subliminal Priming Images Impact Conscious Perception of Facial Expressions

We investigated, in young healthy participants, how the affective content of subliminally presented priming images and their specific visual attributes impacted conscious perception of facial expressions. The priming images were broadly categorized as aggressive, pleasant, or neutral and further subcategorized by the presence of a face and by the centricity (egocentric or allocentric vantage-point) of the image content. Participants responded to the emotion portrayed in a pixelated target-face by indicating via key-press if the expression was angry or neutral. Response time to the neutral target face was significantly slower when preceded by face primes, compared to non-face primes (p < 0.05, Bonferroni corrected). In contrast, faster RTs were observed when angry target faces were preceded by face compared to non-face primes. In addition, participants’ performance was worse when a priming image contained an egocentric face compared to when it contained either an allocentric face or an egocentric non-face. The results suggest a significant impact of the visual features of the priming image on conscious perception of face expression.

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.

Study of Visual Perception and Working Memory in Moroccan Adolescents Attending School

Visual Perception and working memory are essential neuropsychological skills for any learning. The objective of this research is to study these skills, by analyzing numerical plots, according to gender, age, level of study and the stream by evaluating perceptive and memory deficits in Moroccan adolescents attending school. Our sample contains 146 high school students, including 78 boys and 68 girls participated in this study and we used the numerical version of The Rey-Osterrieth complex figure test (ROCF-A) to assess visual perception and working memory. The results of this study showed that, on the one hand, more than 34% of the subjects examined show signs of perceptual deficit and more 21% show signs of memory deficit and, on the other hand, that the scores of the visual perception are significantly associated with age and that working memory scores are significantly associated with age, level of education, and stream.

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.

People＇s Visual Perceptions of Tourism Buildings and Their Environments

The visual and aesthetic aspects of any object are defined by its color, texture, line, and form as well as compositional reference elements such as scale and spatial location in the three-dimensional context. Different methodologies have been developed to conduct visual assessments, based on analyses of the physical, aesthetic, and psychological attributes of the landscape. In this study, relationships between tourism buildings and the environment were analyzed across the perceived landscape and main shopping streets in terms of their color, texture, line and form, scale, and spatial location. Photographic-based questionnaires were administered in Kemer （near Antalya, Turkey） and Knokke （near Brugge, Belgium）. In each location, 30 photographs taken of the coast and principal shopping streets were shown to 100 respondents of different ages, educational backgrounds, and nationalities. Two questions were then asked regarding the visual relationships in the photographs. Six questions regarding socioeconomic characteristics of the respondents were also asked. In both locations, the respondents preferred natural landscapes with few structures, and tourist resorts characterized by small, low-rise, and traditional buildings. The results of this study may provide suggestions for building and landscape architects about how to successfully integrate tourism buildings into the landscape

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.

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.

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.

SAR Image Quality Assessment System Based on Human Visual Perception for Aircraft Electromagnetic Countermeasures

In electronic confrontation, Synthetic Aperture Radar (SAR) is vulnerable to different types of electronic jamming. The research on SAR jamming image quality assessment can provide the prerequisite for SAR jamming and anti-jamming technology, which is an urgent problem that researchers need to solve. Traditional SAR image quality assessment metrics analyze statistical error between the reference image and the jamming image only in the pixel domain; therefore, they cannot reflect the visual perceptual property of SAR jamming images effectively. In this demo, we develop a SAR image quality assessment system based on human visual perception for the application of aircraft electromagnetic countermeasures simulation platform.The internet of things and cloud computing techniques of big data are applied to our system. In the demonstration, we will present the assessment result interface of the SAR image quality assessment system.

3D Perception Algorithms: Towards Perceptually Driven Compression of 3D Video

In this paper, we summarize 3D perception-oriented algorithms for perceptually driven 3D video coding. Several perceptual ef- fects have been exploited for 2D video viewing; however, this is not yet the case for 3D video viewing. 3D video requires depth perception, which implies binocular effects such as con fl icts, fusion, and rivalry. A better understanding of these effects is necessary for 3D perceptual compression, which provides users with a more comfortable visual experience for video that is de- livered over a channel with limited bandwidth. We present state-of-the-art of 3D visual attention models, 3D just-notice- able difference models, and 3D texture-synthesis models that address 3D human vision issues in 3D video coding and trans-mission.

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.