scholarly journals Constant curvature modeling of abstract shape representation

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0254719
Author(s):  
Nicholas Baker ◽  
Philip J. Kellman
Keyword(s):  
Visual System ◽  
Constant Curvature ◽  
Shape Representation ◽  
Recognition Task ◽  
Human Perception ◽  
Human Visual Perception ◽  
Abstract Shape ◽  
Perceptual Performance ◽  
Parameterized Model ◽  
Shape Descriptions

How abstract shape is perceived and represented poses crucial unsolved problems in human perception and cognition. Recent findings suggest that the visual system may encode contours as sets of connected constant curvature segments. Here we describe a model for how the visual system might recode a set of boundary points into a constant curvature representation. The model includes two free parameters that relate to the degree to which the visual system encodes shapes with high fidelity vs. the importance of simplicity in shape representations. We conducted two experiments to estimate these parameters empirically. Experiment 1 tested the limits of observers’ ability to discriminate a contour made up of two constant curvature segments from one made up of a single constant curvature segment. Experiment 2 tested observers’ ability to discriminate contours generated from cubic splines (which, mathematically, have no constant curvature segments) from constant curvature approximations of the contours, generated at various levels of precision. Results indicated a clear transition point at which discrimination becomes possible. The results were used to fix the two parameters in our model. In Experiment 3, we tested whether outputs from our parameterized model were predictive of perceptual performance in a shape recognition task. We generated shape pairs that had matched physical similarity but differed in representational similarity (i.e., the number of segments needed to describe the shapes) as assessed by our model. We found that pairs of shapes that were more representationally dissimilar were also easier to discriminate in a forced choice, same/different task. The results of these studies provide evidence for constant curvature shape representation in human visual perception and provide a testable model for how abstract shape descriptions might be encoded.

scholarly journals Forensic Engineering Issues In Glare And Visibility Studies

2006 ◽  
Vol 23 (2) ◽  
Author(s):  
Adam K. Aleksander
Keyword(s):  
Visual System ◽  
Human Visual System ◽  
San Diego ◽  
Human Perception ◽  
Short Paper ◽  
Forensic Engineering ◽  
Common Items

Forensic Engineering Evaluation Of Visibility Related Issues In The Night Driving Environment Requires The Understanding Of A Range Of Phenomena, Including The Human Visual System, The Nature Of Light, The Measurement Of Light, And The Limitations Of Human Perception. This Short Paper Outlines The Pertinent Topical Areas, And Is Intended To Supplement A More Detailed Discussion Presented At The Nafe Meeting In January 2005 In San Diego. Although Many Important Vision Concepts Are Omitted, The Forensic Engineer Will Gain An Appreciation Of The Fundamental Issues. Results Of Visibility Tests On Some Common Items Are Presented To Guide The Reader, And To Correlate With Other Data They May Encounter In Their Individual Practice. Three Cases Are Discussed, Which Include The Elements Of Night Driving, Glare, Conspicuity, Contrast, And Human Perception And Reaction.

Invariant Recognition Shapes Neural Representations of Visual Input

2018 ◽  
Vol 4 (1) ◽  
pp. 403-422 ◽  
Author(s):  
Andrea Tacchetti ◽  
Leyla Isik ◽  
Tomaso A. Poggio
Keyword(s):  
Computational Neuroscience ◽  
Sensory Input ◽  
Human Perception ◽  
Visual Input ◽  
Crucial Aspect ◽  
Human Visual Perception ◽  
Semantic Categories ◽  
Neural Representations ◽  
The People ◽  
The World

Recognizing the people, objects, and actions in the world around us is a crucial aspect of human perception that allows us to plan and act in our environment. Remarkably, our proficiency in recognizing semantic categories from visual input is unhindered by transformations that substantially alter their appearance (e.g., changes in lighting or position). The ability to generalize across these complex transformations is a hallmark of human visual intelligence, which has been the focus of wide-ranging investigation in systems and computational neuroscience. However, while the neural machinery of human visual perception has been thoroughly described, the computational principles dictating its functioning remain unknown. Here, we review recent results in brain imaging, neurophysiology, and computational neuroscience in support of the hypothesis that the ability to support the invariant recognition of semantic entities in the visual world shapes which neural representations of sensory input are computed by human visual cortex.

scholarly journals Preserved capacity for learning statistical regularities and directing selective attention after hippocampal lesions

2019 ◽  
Vol 116 (39) ◽  
pp. 19705-19710 ◽  
Author(s):  
Nuttida Rungratsameetaweemana ◽  
Larry R. Squire ◽  
John T. Serences
Keyword(s):  
Information Processing ◽  
Prior Knowledge ◽  
Human Perception ◽  
Motion Direction ◽  
Hippocampal Lesions ◽  
Perceptual Performance ◽  
Statistical Regularities ◽  
Probabilistic Structure ◽  
Sensory Evidence ◽  
Task Conditions

Prior knowledge about the probabilistic structure of visual environments is necessary to resolve ambiguous information about objects in the world. Expectations based on stimulus regularities exert a powerful influence on human perception and decision making by improving the efficiency of information processing. Another type of prior knowledge, termed top-down attention, can also improve perceptual performance by facilitating the selective processing of relevant over irrelevant information. While much is known about attention, the mechanisms that support expectations about statistical regularities are not well-understood. The hippocampus has been implicated as a key structure involved in or perhaps necessary for the learning of statistical regularities, consistent with its role in various kinds of learning and memory. Here, we tested this hypothesis using a motion discrimination task in which we manipulated the most likely direction of motion, the degree of attention afforded to the relevant stimulus, and the amount of available sensory evidence. We tested memory-impaired patients with bilateral damage to the hippocampus and compared their performance with controls. Despite a modest slowing in response initiation across all task conditions, patients performed similar to controls. Like controls, patients exhibited a tendency to respond faster and more accurately when the motion direction was more probable, the stimulus was better attended, and more sensory evidence was available. Together, these findings demonstrate a robust, hippocampus-independent capacity for learning statistical regularities in the sensory environment in order to improve information processing.

scholarly journals Improving the performance of the amblyopic visual system

2008 ◽  
Vol 364 (1515) ◽  
pp. 399-407 ◽  
Author(s):  
Dennis M Levi ◽  
Roger W Li
Keyword(s):  
Visual System ◽  
Perceptual Learning ◽  
Neural Plasticity ◽  
Time Course ◽  
Clinical Evidence ◽  
Sensory Function ◽  
Sensitive Period ◽  
Visual Improvement ◽  
Perceptual Performance ◽  
Effectiveness And Efficiency

Experience-dependent plasticity is closely linked with the development of sensory function; however, there is also growing evidence for plasticity in the adult visual system. This review re-examines the notion of a sensitive period for the treatment of amblyopia in the light of recent experimental and clinical evidence for neural plasticity. One recently proposed method for improving the effectiveness and efficiency of treatment that has received considerable attention is ‘perceptual learning’. Specifically, both children and adults with amblyopia can improve their perceptual performance through extensive practice on a challenging visual task. The results suggest that perceptual learning may be effective in improving a range of visual performance and, importantly, the improvements may transfer to visual acuity. Recent studies have sought to explore the limits and time course of perceptual learning as an adjunct to occlusion and to investigate the neural mechanisms underlying the visual improvement. These findings, along with the results of new clinical trials, suggest that it might be time to reconsider our notions about neural plasticity in amblyopia.

scholarly journals Garment smoothness appearance evaluation through computer vision

2011 ◽  
Vol 82 (3) ◽  
pp. 299-309 ◽  
Author(s):  
Javier Silvestre-Blanes ◽  
Joaquin Berenguer-Sebastiá ◽  
Rubén Pérez-Lloréns ◽  
Ignacio Miralles ◽  
Jorge Moreno
Keyword(s):  
Computer Vision ◽  
Visual System ◽  
Human Visual System ◽  
Evaluation System ◽  
Human Perception ◽  
Measurement And Evaluation ◽  
Different Parts ◽  
Textile Products

The measurement and evaluation of the appearance of wrinkling in textile products after domestic washing and drying is performed currently by the comparison of the fabric with the replicas. This kind of evaluation has certain drawbacks, the most significant of which are its subjectivity and its limitations when used with garments. In this paper, we present an automated wrinkling evaluation system. The system developed can process fabrics as well as any type of garment, independent of size or pattern on the material. The system allows us to label different parts of the garment. Thus, as different garment parts have different influence on human perception, this labeling enables the use of weighting, to improve the correlation with the human visual system. The system has been tested with different garments showing good performance and correlation with human perception.

scholarly journals Mobile Robot Navigation Based on Circle Recognition

2013 ◽  
Vol 64 (2) ◽  
pp. 84-91 ◽  
Author(s):  
Peter Pásztó ◽  
Peter Hubinský
Keyword(s):  
Image Processing ◽  
Visual System ◽  
Mobile Robot ◽  
Trajectory Planning ◽  
Relative Position ◽  
Robot Navigation ◽  
Recognition Task ◽  
Mobile Robot Navigation ◽  
Planning Algorithm ◽  
Navigation Method

This paper presents a navigation method for a mobile robot using a visual system. Circular marks with specific colors are used for marking the significant points of the mobile robot’s trajectory that it needs to pass. The colors of the used marks are signalizing the way of their bypassing with the mobile robot (from the left or right side). The mobile robot uses only one camera for the marks recognition task and it is able to determine its own relative position from the detected marks. The image processing and the mobile robot’s trajectory planning algorithm working in real-time are described in this paper.

scholarly journals Temporal Properties of Abstract Shape Representation

2016 ◽  
Vol 16 (12) ◽  
pp. 789
Author(s):  
Nicholas Baker ◽  
Philip Kellman
Keyword(s):  
Shape Representation ◽  
Temporal Properties ◽  
Abstract Shape

scholarly journals Familiarity increases processing speed in the visual system

2019 ◽  
Author(s):  
Mariya E. Manahova ◽  
Eelke Spaak ◽  
Floris P. de Lange
Keyword(s):  
Visual System ◽  
Brain Activity ◽  
Spatial Dynamics ◽  
Neural Response ◽  
Visual Response ◽  
Neural Responses ◽  
Visual Stream ◽  
Perceptual Performance ◽  
Evoked Activity ◽  
Human Participants

AbstractFamiliarity with a stimulus leads to an attenuated neural response to the stimulus. Alongside this attenuation, recent studies have also observed a truncation of stimulus-evoked activity for familiar visual input. One proposed function of this truncation is to rapidly put neurons in a state of readiness to respond to new input. Here, we examined this hypothesis by presenting human participants with target stimuli that were embedded in rapid streams of familiar or novel distractor stimuli at different speeds of presentation, while recording brain activity using magnetoencephalography (MEG) and measuring behavioral performance. We investigated the temporal and spatial dynamics of signal truncation and whether this phenomenon bears relationship to participants’ ability to categorize target items within a visual stream. Behaviorally, target categorization performance was markedly better when the target was embedded within familiar distractors, and this benefit became more pronounced with increasing speed of presentation. Familiar distractors showed a truncation of neural activity in the visual system, and this truncation was strongest for the fastest presentation speeds. Moreover, neural processing of the target was stronger when it was preceded by familiar distractors. Taken together, these findings suggest that truncation of neural responses for familiar items may result in stronger processing of relevant target information, resulting in superior perceptual performance.Significance statementThe visual response to familiar input is attenuated more rapidly than for novel input. Here we find that this truncation of the neural response for familiar input is strongest for very fast image presentations. We also find a tentative function for this truncation: the neural response to a target image that is embedded within distractors is much greater when the distractors are familiar than when they are novel. Similarly, target categorization performance is much better when the target is embedded within familiar distractors, and this advantage is most obvious for very fast image presentations. This suggests that neural truncation helps to rapidly put neurons in a state of readiness to respond to new input.

scholarly journals Steganography Based on Human Perception

2017 ◽  
Vol 10 (04) ◽  
pp. 817-823
Author(s):  
Suman Chakraborty ◽  
Anil Bikash Chowdhury
Keyword(s):  
Social Media ◽  
Visual Perception ◽  
Credit Card ◽  
Personal Information ◽  
Human Perception ◽  
Human Visual Perception ◽  
Governance System ◽  
Information Shares ◽  
The Government ◽  
Almost All

Today internet has become a trusted factotum of everyone. Almost all payments like tax, insurance, bank transaction, healthcare payment, payment in e-commerce are done digitally through debit or credit card or through e-wallet. People share their personal information through social media like Facebook. Twitter, WhatsApp etc. The government of every developing country is going to embrace e-Governance system to interact with people more promptly. The information shares through these applications are the burning target to intruders. This paper utilized the imperceptibility as well as the robustness of steganography techniques which are increased by embedding multiple bits in a particular region selected either based on some image attributes or by Human Visual Perception.

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