Representation Of Visual Information Research Articles

Prediction error and repetition suppression have distinct effects on neural representations of visual information.

Predictive coding theories argue that recent experience establishes expectations in the brain that generate prediction errors when violated. Prediction errors provide a possible explanation for repetition suppression, where evoked neural activity is attenuated across repeated presentations of the same stimulus. The predictive coding account argues repetition suppression arises because repeated stimuli are expected, whereas non-repeated stimuli are unexpected and thus elicit larger neural responses. Here, we employed electroencephalography in humans to test the predictive coding account of repetition suppression by presenting sequences of visual gratings with orientations that were expected either to repeat or change in separate blocks of trials. We applied multivariate forward modelling to determine how orientation selectivity was affected by repetition and prediction. Unexpected stimuli were associated with significantly enhanced orientation selectivity, whereas selectivity was unaffected for repeated stimuli. Our results suggest that repetition suppression and expectation have separable effects on neural representations of visual feature information.

Representing the Presence of Absence in Cartography

A key cartographic challenge associated with the rise of big data is to show when spatial data observations are missing or to communicate variables that indicate absence. For example, showing where people are tweeting during a disaster might be interesting, but visually identifying where normal signals are missing could in fact highlight the most affected places. Parcel data might be fully present, but attributes of their observations could convey qualities of absence (e.g., abandoned structures). Current geovisualization approaches normally do not show anything at all when data are missing or contain qualities of absence and only in rare cases might use a specific hue to highlight the presence of absence on maps. This work argues that people perceive missingness and absence in a way that is distinct from other spatial data qualities, and we propose a typology of static and dynamic means by which we can draw user attention to the presence of absence. To explore the application of these techniques, I use urban parcel data to visualize patterns of property blight in a Detroit neighborhood. Based on conceptual development and case study application, I propose research challenges to evaluate visual representations of missing and absent information on maps.

Blind image quality assessment with hierarchy: Degradation from local structure to deep semantics

Though blind image quality assessment (BIQA) is highly desired in perceptual-oriented image processing systems, it is extremely difficult to design a reliable BIQA method. With the help of the prior knowledge, the human visual system (HVS) hierarchically perceives the quality degradation during the visual recognition. Inspired by this, we suggest different levels of distortion generate individual degradations on hierarchical features, and propose to consider the degradations on both low and high level features for quality prediction. By mimicking the orientation selectivity (OS) mechanism in the primary visual cortex, an OS based local structure is designed for low-level visual information representation. At the meantime, the deep residual network, which possesses multiple levels for feature integration, is employed to extract the deep semantics for high-level visual content representation. By fusing the local structure and the deep semantics, a hierarchical feature set is acquired. Next, the correlations between the degradations of image qualities and their corresponding hierarchical feature sets are analyzed, and a novel hierarchical feature degradation (HFD) based BIQA (HFD-BIQA) method is built. Experimental results on the legacy and wild image quality assessment databases demonstrate the prediction accuracy of the proposed HFD-BIQA method, and verify that the HFD-BIQA performs highly consistent with the subjective perception.

A principle of designing infographic for visualization representation of tourism social big data

With the development of technology, people have more needs for the visual representation of interface information. Visualization, image and interaction have all become the design directions of user interfaces in recent years. The purpose of this study is to collect the user’s perception of the chart through experiments, explore the visualization of the chart presentation, and establish the “The principle of infographic design”. This study used the Octopus web data collection software to collect travel-related social big data of Facebook fan page and produce six different types of charts (a total of ten charts) by Tableau visual software that used as the experimental chart material. Relevant visual factors were derived through experiments. The experimental results found the chart element size, color, color gradients, data, sorting, and chart title will affect the results of the user to watch the chart. This study suggests the following induction 4 points to establish the presentation of information charts to provide chart designer: (1) to appropriate use of color to show the infographic, (2) marked the data to help users quickly understand the information, (3) sort the size of the element, so that users can have a sequential view, and (4) make the best use of different sizes, to convey the difference in the proportion of users.

Dissociating parallel and serial processing of numerical value

Digits serve as useful tools for studying the interaction between low-level perceptual representations and higher-level semantic information, and also the degree to which processing these stimulus attributes relies on similar or different mechanisms. Following a body of literature that debates the influence of high-level, semantic information on perceptual processing, and work by Van Opstal and colleagues (2011) investigating whether subliminally presented digit arrays affect estimates of numerical averages, here we explored the temporal dynamics of extracting numerical values associated with each digit in an array. Specifically, we examined reaction times (RTs) for estimating the average of digit arrays of varying sizes to determine whether numerical meaning is extracted in parallel, or instead may require serial processing of individual digits. In Experiment 1, participants completed a numerical mean estimation task, along with visual search tasks designed to yield RT patterns across increasing display sizes thought to be characteristic of serial and parallel processes. In Experiment 2, we controlled for brightness cues that could have contributed to performance in Experiment 1. In both experiments, comparing RT patterns for the numerical averaging tasks to those of the search tasks suggested that semantic information from multiple digits may be extracted by a parallel processing mechanism. Unlike in either search task, RTs improved with increasing display size, indicating a potential benefit of larger displays as has been reported for extracting ensemble, or summary statistical representations of lower-level visual information.

A Tale of Two Visual Systems: Invariant and Adaptive Visual Information Representations in the Primate Brain.

Visual information processing contains two opposite needs. There is both a need to comprehend the richness of the visual world and a need to extract only pertinent visual information to guide thoughts and behavior at a given moment. I argue that these two aspects of visual processing are mediated by two complementary visual systems in the primate brain-specifically, the occipitotemporal cortex (OTC) and the posterior parietal cortex (PPC). The role of OTC in visual processing has been documented extensively by decades of neuroscience research. I review here recent evidence from human imaging and monkey neurophysiology studies to highlight the role of PPC in adaptive visual processing. I first document the diverse array of visual representations found in PPC. I then describe the adaptive nature of visual representation in PPC by contrasting visual processing in OTC and PPC and by showing that visual representations in PPC largely originate from OTC.

ICtCp Versus Y'CbCr: Evaluation of ICtCp Color Space and an Adaptive Reshaper for HDR and WCG

New emerging technologies in the field of multimedia, such as high dynamic range (HDR) and wide color gamut (WCG), challenge the performance of existing image and video data processing algorithms, especially in terms of visual data compression and its faithful representation. HDR and WCG offer the technological capabilities to capture and represent a scene with an extended amount of details in both luminance and chrominance, respectively. This article presents and evaluates possible solutions to cope with such an extensive amount of data while delivering a faithful representation of visual information. More particularly, two approaches proposing novel color space, a constant intensity color difference signal representation called ICtCp and a novel compression optimization algorithm called the reshaper, are described and subjectively evaluated. The results of the conducted experiments show competitive performance of the two proposed approaches, ICtCp and reshaper, allowing a 10% bit rate reduction while preserving the perceived quality.

Visual mental imagery influences attentional guidance in a visual-search task.

Visual mental imagery resembles visual working memory (VWM). Because both visual mental imagery and VWM involve the representation and manipulation of visual information, it was hypothesized that they would exert similar effects on visual attention. Several previous studies have demonstrated that working-memory representations guide attention toward a memory-matching task-irrelevant stimulus during visual-search tasks. Therefore, mental imagery may also guide attention toward imagery-matching stimuli. In the present study, five experiments were conducted to investigate the effects of visual mental imagery on visual attention during a visual-search task. Participants were instructed to visualize a color or an object clearly associated with a specific color, after which they were asked to detect a colored target in the visual-search task. Reaction times for target detection were shorter when the color of the target matched the imagined color, and when the color of the target was similar to that strongly associated with the imagined object, than when the color of the target did not match that of the mental representation. This effect was not observed when participants were not instructed to imagine a color. These results suggest that similar to VWM, visual mental imagery guides attention toward imagery-matching stimuli.

The Role of Infographics for the Development of Skills for Cognitive Modeling in Education

Contemporary culture is a visual culture. Visual images become the predominant form of communication. Students should be visually literate and be able to read and use visual language, to decode, interpret and evaluate visual messages successfully, and, last but not least, to encode and compose meaningful visual communication. The combination of modeling with other methods in scientific knowledge increases its potential as a cognitive method. Infographics can play a significant role in the process as tool or target according to the age and cognitive abilities of the students. Information images (infographics) are visual representations of information, data or knowledge. The use of infographics as a modeling method can develop different cognitive skills such as interpretation, analysis, assessment, conclusion, explanation, which are all part of the modeling process. In fact, they can be a tool for achieving the next stage of literacy - visual literacy. All this necessitates the exploration of infographics as an instrument in the development of a comprehensive system of cognitive tasks in education related to the formation of skills for modeling. In the paper, six types of cognitive tasks in education are analyzed as well as their relation to the visual literacy competence standards approved by the Association of College & Research Libraries. A comparison of freely available infographics tools is provided and the suitability of different infographics templates is discussed.

Visual representation of medical information: the importance of considering the end-user in the design of medical illustrations

This practice led research project explored visual representation through illustrations designed to communicate often complex medical information for different users within Auckland City Hospital, New Zealand. Media and tools were manipulated to affect varying degrees of naturalism or abstraction from reality in the creation of illustrations for a variety of real-life clinical projects, and user feedback on illustration preference gathered from both medical professionals and patients. While all users preferred the most realistic representations of medical information from the illustrations presented, patients often favoured illustrations that depicted a greater amount of information than professionals suggested was necessary.

COMPLEX SOFTWARE FORCOLLECTION AND VISUALIZATION OF SOFTWARE DEFECTS STATISTICS

In the article the data requirements for construction of the reliability model of the software system are considered. Using UML class diagrams, we describe the processes of collecting, analyzing and visual representation of information on the number of defects registered on projects. The developed software package, based on the requirements, will provide the opportunity to conduct further research on the simulation of the reliability of software systems, taking into account the number of defects and the time of their registration in accordance with the duration of the project. It is planned to carry out a detailed analysis of the collected data in order to determine the patterns of dependence of the number of defects on the various project characteristics (complexity of the architecture, duration of the project, number of testers, number of developers). Most software system reliability models use a limited (not complete) number of project characteristics that affect the reliability of the software, so it is planned to analyze the existing software product reliability models and verify them on the collected data in order to determine the additional characteristics of the project, which is needed, but take into account for modeling the reliability of a software product

A Virtual Geographic Environment for Debris Flow Risk Analysis in Residential Areas

Emergency risk assessment of debris flows in residential areas is of great significance for disaster prevention and reduction, but the assessment has disadvantages, such as a low numerical simulation efficiency and poor capabilities of risk assessment and geographic knowledge sharing. Thus, this paper focuses on the construction of a VGE (virtual geographic environment) system that provides an efficient tool to support the rapid risk analysis of debris flow disasters. The numerical simulation, risk analysis, and 3D (three-dimensional) dynamic visualization of debris flow disasters were tightly integrated into the VGE system. Key technologies, including quantitative risk assessment, multiscale parallel optimization, and visual representation of disaster information, were discussed in detail. The Qipan gully in Wenchuan County, Sichuan Province, China, was selected as the case area, and a prototype system was developed. According to the multiscale parallel optimization experiments, a suitable scale was chosen for the numerical simulation of debris flow disasters. The computational efficiency of one simulation step was 5 ms (milliseconds), and the rendering efficiency was approximately 40 fps (frames per second). Information about the risk area, risk population, and risk roads under different conditions can be quickly obtained. The experimental results show that our approach can support real-time interactive analyses and can be used to share and publish geographic knowledge.

Visualization during Crystallization in Minkowski Spacetime

It was achieved a visual representation of information about the crystallization process in the multidimensional space, which creates prerequisites for the development of software systems to solve a wide class of problems. With the geometric interpretation Minkowski space-time, quasi-Lorentz and Einstein's concept concerning the concept of giving time physical sense, simulated the process of formation of crystals in the four-dimensional space. The 4D model space combines the physical three-dimensional space of the factors affecting the formation of crystals, and time. Visualization of the crystallization process in spacetime plays an important role, as having great cognitive and probative value, and contributes to a better understanding of crystallization processes, creates conditions to control the properties of materials in the process of crystallization.

Task-context-dependent Linear Representation of Multiple Visual Objects in Human Parietal Cortex.

A host of recent studies have reported robust representations of visual object information in the human parietal cortex, similar to those found in ventral visual cortex. In ventral visual cortex, both monkey neurophysiology and human fMRI studies showed that the neural representation of a pair of unrelated objects can be approximated by the averaged neural representation of the constituent objects shown in isolation. In this study, we examined whether such a linear relationship between objects exists for object representations in the human parietal cortex. Using fMRI and multivoxel pattern analysis, we examined object representations in human inferior and superior intraparietal sulcus, two parietal regions previously implicated in visual object selection and encoding, respectively. We also examined responses from the lateral occipital region, a ventral object processing area. We obtained fMRI response patterns to object pairs and their constituent objects shown in isolation while participants viewed these objects and performed a 1-back repetition detection task. By measuring fMRI response pattern correlations, we found that all three brain regions contained representations for both single object and object pairs. In the lateral occipital region, the representation for a pair of objects could be reliably approximated by the average representation of its constituent objects shown in isolation, replicating previous findings in ventral visual cortex. Such a simple linear relationship, however, was not observed in either parietal region examined. Nevertheless, when we equated the amount of task information present by examining responses from two pairs of objects, we found that representations for the average of two object pairs were indistinguishable in both parietal regions from the average of another two object pairs containing the same four component objects but with a different pairing of the objects (i.e., the average of AB and CD vs. that of AD and CB). Thus, when task information was held consistent, the same linear relationship may govern how multiple independent objects are represented in the human parietal cortex as it does in ventral visual cortex. These findings show that object and task representations coexist in the human parietal cortex and characterize one significant difference of how visual information may be represented in ventral visual and parietal regions.

The Mechanisms of Psychedelic Visionary Experiences: Hypotheses from Evolutionary Psychology.

Neuropharmacological effects of psychedelics have profound cognitive, emotional, and social effects that inspired the development of cultures and religions worldwide. Findings that psychedelics objectively and reliably produce mystical experiences press the question of the neuropharmacological mechanisms by which these highly significant experiences are produced by exogenous neurotransmitter analogs. Humans have a long evolutionary relationship with psychedelics, a consequence of psychedelics' selective effects for human cognitive abilities, exemplified in the information rich visionary experiences. Objective evidence that psychedelics produce classic mystical experiences, coupled with the finding that hallucinatory experiences can be induced by many non-drug mechanisms, illustrates the need for a common model of visionary effects. Several models implicate disturbances of normal regulatory processes in the brain as the underlying mechanisms responsible for the similarities of visionary experiences produced by psychedelic and other methods for altering consciousness. Similarities in psychedelic-induced visionary experiences and those produced by practices such as meditation and hypnosis and pathological conditions such as epilepsy indicate the need for a general model explaining visionary experiences. Common mechanisms underlying diverse alterations of consciousness involve the disruption of normal functions of the prefrontal cortex and default mode network (DMN). This interruption of ordinary control mechanisms allows for the release of thalamic and other lower brain discharges that stimulate a visual information representation system and release the effects of innate cognitive functions and operators. Converging forms of evidence support the hypothesis that the source of psychedelic experiences involves the emergence of these innate cognitive processes of lower brain systems, with visionary experiences resulting from the activation of innate processes based in the mirror neuron system (MNS).

Structured entropy of primitive: big data‐based stereoscopic image quality assessment

The ultimate receiver of image and video is human visual system (HVS). It is an important problem in the domain of image and video processing that how to establish visual information representation model meeting the HVS perception property. In this study, authors give theory analysis and experiment results to prove that l_1 norm-based entropy of primitive (EoP) is superior to the l_0 norm-based EoP for the monocular cue in image quality assessment. By developing the concept of mutual information of primitive (MIP) as the binocular cue, an l_1 EoP-based stereoscopic image quality assessment metric is proposed. With EoP as monocular cue and MIP as binocular cue, the relative entropy between the original stereoscopic image and the distorted one is explored to predict the quality score with support vector regression. To avoid destroying image's structured information, the structured EoP (SEoP) is further explored to measure the stereoscopic image information. Extensive experimental results demonstrate that the stereoscopic image quality assessment algorithm with SEoP as monocular cue and MIP as binocular cue outperforms many state-of-the-art ones.

Task relevance modulates the cortical representation of feature conjunctions in the target template

Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template maintenance prior to visual search. Subjects were cued to search for a spatial frequency (SF) or orientation of a Gabor grating and we measured BOLD signal during cue and delay periods before the onset of a search display. RSA of delay period activity revealed that widespread regions in frontal, posterior parietal, and occipitotemporal cortices showed general representational differences between task relevant and task irrelevant dimensions (e.g., orientation vs. SF). In contrast, RSA of cue period activity revealed sensory-related representational differences between cue images (regardless of task) at the occipital pole and additionally in the frontal pole. Our data show that task and sensory information are represented differently during viewing and during target template maintenance, and that task relevance modulates the representation of visual information across the cortex.

A Research-Based Evidence of the Effect of Graphic Organizers on the Understanding of Prose Fiction in ESL Classroom

Graphic organizers (GOs) are fast becoming acceptable standard instructional tools across subjects in the education arena globally. However, this visual representation of information is yet to be recognized and integrated into the teaching methods in Nigerian schools. This study, therefore, presents a research-based investigation of the usefulness of GOs in the appreciation of prose literature in Nigeria, with a view to foregrounding their use in Nigerian schools. Specifically, the study seeks to find out whether senior secondary students in prose literature-in-English in Nigeria who are taught with GOs perform better in prose and comprehension assessments. Four project secondary schools with total of 100 students were purposively selected for the study. The schools were grouped into two: graphic-based schools (GBS) and non-graphic-based schools (NGBS). Whereas the GBS was exposed to instruction via eight graphic organizers, the NGBS served as control. Subjected to descriptive statistics and one-sample t test analysis, the investigation reveals that graphic organizers make students take charge of the learning process in prose literature classes, and it concludes that these visual instructional elements guarantee student understanding and achievement. The study, thus, recommends the incorporation of graphic organizers in the teaching and learning processes across subjects in Nigerian schools.

A visual interaction consensus model for social network group decision making with trust propagation

A theoretical visual interaction framework to model consensus in social network group decision making (SN-GDM) is put forward with following three main components: (1) construction of trust relationship; (2) trust based recommendation mechanism; and (3) visual adoption mechanism. To do that, dual trust propagation is investigated to connect incomplete trust relationship by trusted third partners, in a way that it can fit our intuition in these cases: trust values decrease while distrust values increase. Trust relationship is proposed to be used in determining the trust degree of experts and in aggregating individual opinions into a collective one. Three levels of consensus degree are defined and used to identify the inconsistent experts. A trust based recommendation mechanism is developed to generate advices according to individual trust relationship, making recommendations more likeable to be implemented by the inconsistent experts to achieve higher levels of consensus. Therefore, it has an advantage with respect to existing interaction models because it does not force the inconsistent experts to accept advices irrespective of their trust on them. Finally, a visual adoption mechanism, which provides visual information representations on experts’ individual consensus positions before and after adopting the recommendation advices, is presented and analysed theoretically. Experts can select their appropriate feedback parameters to achieve a balance between group consensus and individual independence. Consequently, the proposed visual interaction model adds real and needed flexibility in guiding the consensus reaching process in SN-GDM.

A complementary square-error clustering criterion and initialization of K-means

EC3 is intended to extract relevant information from large heterogeneous and multilingual text data, in particular in WEB 3.0. The project is based on an original method: contextual exploration. EC3 does not need syntactic analysis, statistical analysis or a general ontology. EC3 uses only small called ontologies that express the linguistic knowledge of a user who must concentrate on the relevant information from one point of view. This is why EC3 works very quickly on large corpus, whose components can be both whole books as well as short texts: SMS to books. At the output, EC3 offers a visual representation of information using an original approach: the Memory Islands. EC3 is implanted in the ACASA / LIP6 team. EC3 is tested on the large digitized corpus provided by the Labex OBVIL «Observatoire de la Vie Litteraire», in partnership with the Bibliotheque Nationale de France (http://obvil.paris-sorbonne.fr/). OBVIL intends to develop all the resources offered by digitization and computer applications to examine French literature from the sixteenth to the twentieth century, English and American literature, Italian literature, Spanish literature, in its most traditional formats and media Or the most innovative.