Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Lightness (6)
- Attention (5)
- Signal detection theory (5)
- Material perception (4)
- Vision (4)
-
- Visual search (4)
- Free-viewing (3)
- Neural networks (3)
- Psychophysics (3)
- Saliency (3)
- Symmetry (3)
- Biased competition (2)
- Classification images (2)
- Clustering (2)
- Color (2)
- Computational modeling (2)
- Contrast gain control (2)
- Contrast sensitivity (2)
- Edge integration (2)
- Eye movements (2)
- Fixational eye movements (2)
- Gestalt (2)
- Image segmentation (2)
- Material Perception (2)
- Motion (2)
- Neural model (2)
- Object recognition (2)
- Orientation (2)
- Perception (2)
- Perceptual organization (2)
Articles 1 - 30 of 94
Full-Text Articles in Social and Behavioral Sciences
Euclidean Coordinates Are The Wrong Prior For Models Of Primate Vision, Garrison W. Cottrell
Euclidean Coordinates Are The Wrong Prior For Models Of Primate Vision, Garrison W. Cottrell
MODVIS Workshop
Convolutional Neural Networks (CNNs) are currently the best models we have of the ventral temporal lobe – the part of cortex engaged in recognizing objects. They have been effective at predicting the firing rates of neurons in monkey cortex, as well as fMRI and MEG responses in human subjects. They are based on several observations concerning the visual world: 1) pixels are most correlated with nearby pixels, leading to local receptive fields; 2) stationary statistics – the statistics of image pixels are relatively invariant across the visual field, leading to replicated features 3) objects do not change identity depending on …
Extreme Image Transformations Improve Latent Representations In Machines, Girik Malik, Ennio Mingolla
Extreme Image Transformations Improve Latent Representations In Machines, Girik Malik, Ennio Mingolla
MODVIS Workshop
Shuffling pixels in an image helps machines to learn a more robust object representation. To probe the strategies used by humans and machines for object recognition, we introduce Extreme Image Transformations (EITs). Machines rely heavily on exploiting low-level features like color and texture, so their performance degrades on out-of-distribution and adversarial inputs. Humans depend on high-level features like shapes and contours, making them relatively robust to image distortions. EITs systematically shuffle the pixels in an image, parameterized by the size of grids, probability of shuffle and binary block movement, distorting the structure of objects at both local and global levels. …
Anisotropy In Non-Rigidity Perception: The Role Of Anisotropies In Neural Populations, Akihito Maruya, Qasim Zaidi
Anisotropy In Non-Rigidity Perception: The Role Of Anisotropies In Neural Populations, Akihito Maruya, Qasim Zaidi
MODVIS Workshop
No abstract provided.
Do Mechanisms Of Sinusoidal Contrast Sensitivity Account For Edge Sensitivity?, Lynn Schmittwilken, Felix A. Wichmann, Marianne Maertens
Do Mechanisms Of Sinusoidal Contrast Sensitivity Account For Edge Sensitivity?, Lynn Schmittwilken, Felix A. Wichmann, Marianne Maertens
MODVIS Workshop
No abstract provided.
Local Geometry Of Elementary Visual Computations, Peter Neri
Local Geometry Of Elementary Visual Computations, Peter Neri
MODVIS Workshop
Visual operators (e.g. edge detectors) are classically modelled using small circuits involving canonical computations, such as template-matching and gain control. Circuit models explain many aspects of the empirical descriptors that are used to characterize local visual operators, from sensitivity to classification images. Notwithstanding their utility, these models fail to provide a unified framework encompassing the variety of effects observed experimentally, such as the impact of contrast, SNR, and attention on the above descriptors. My goal is to start with a simple, plausible geometrical representation of the perceptual operation carried out by the observer, and to show that this representation is …
Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens
Extracting Edges In Space And Time During Visual Fixations, Lynn Schmittwilken, Marianne Maertens
MODVIS Workshop
No abstract provided.
A Signal Detection Model For The Analysis Of Continuous Response Gradients And An Application To Confidence Rating Data, Fabian A. Soto
A Signal Detection Model For The Analysis Of Continuous Response Gradients And An Application To Confidence Rating Data, Fabian A. Soto
MODVIS Workshop
see attached
Modelling Pairwise Comparisons For Thurstonian Scaling And Kendall Rank Correlation, Maarten Wijntjes
Modelling Pairwise Comparisons For Thurstonian Scaling And Kendall Rank Correlation, Maarten Wijntjes
MODVIS Workshop
Pairwise comparisons are a simple and effective way to measure the relative ordering of two samples. For more than two samples, a global ordering can be constructed and with sufficient data it is possible to construct a metric scale, for example by using Thurstonian scaling. We will discuss the concept of Number of Distinguishable Levels (NDLs) that emerges from a Thurstonian scaling procedure. The NDL is the attribute range in terms of Just Noticeable Differences (JNDs), for example the number of grayscale values. The NDL is either limited by the visual system or by the range of stimuli. The latter …
Constraining The Binding Problem Using Maps, Zhixian Han, Anne Sereno
Constraining The Binding Problem Using Maps, Zhixian Han, Anne Sereno
MODVIS Workshop
We constrained the binding problem by creating maps of different attributes. We compared the performance of different models with different maps in our current study. Our preliminary results showed that the performance of the model is the highest when location maps were used. These results suggest that the optimal way to constrain the binding problem is to create location maps of different attributes.
Evaluating Models Of Scanpath Prediction, Matthias Kümmerer, Matthias Bethge
Evaluating Models Of Scanpath Prediction, Matthias Kümmerer, Matthias Bethge
MODVIS Workshop
No abstract provided.
Modeling The Spread Of Object-Based Attention During Free Viewing, Nicolas Roth, Olga Shurygina, Flora Marleen Muscinelli, Klaus Obermayer, Martin Rolfs
Modeling The Spread Of Object-Based Attention During Free Viewing, Nicolas Roth, Olga Shurygina, Flora Marleen Muscinelli, Klaus Obermayer, Martin Rolfs
MODVIS Workshop
No abstract provided.
A Dynamical Model Of Binding In Visual Cortex During Incremental Grouping And Search, Daniel Schmid, Daniel A. Braun, Heiko Neumann
A Dynamical Model Of Binding In Visual Cortex During Incremental Grouping And Search, Daniel Schmid, Daniel A. Braun, Heiko Neumann
MODVIS Workshop
Binding of visual information is crucial for several perceptual tasks. To incrementally group an object, elements in a space-feature neighborhood need to be bound together starting from an attended location (Roelfsema, TICS, 2005). To perform visual search, candidate locations and cued features must be evaluated conjunctively to retrieve a target (Treisman&Gormican, Psychol Rev, 1988). Despite different requirements on binding, both tasks are solved by the same neural substrate. In a model of perceptual decision-making, we give a mechanistic explanation for how this can be achieved. The architecture consists of a visual cortex module and a higher-order thalamic module. While the …
Object Rigidity: Competition And Cooperation Between Motion-Energy And Feature- Tracking Mechanisms And Shape-Based Priors, Akihito Maruya, Qasim Zaidi Dr.
Object Rigidity: Competition And Cooperation Between Motion-Energy And Feature- Tracking Mechanisms And Shape-Based Priors, Akihito Maruya, Qasim Zaidi Dr.
MODVIS Workshop
No abstract provided.
Efficient Perception Of Physical Object Properties With Visual Heuristics, Vivian C. Paulun, Florian S. Bayer, Joshua B. Tenenbaum, Roland W. Fleming
Efficient Perception Of Physical Object Properties With Visual Heuristics, Vivian C. Paulun, Florian S. Bayer, Joshua B. Tenenbaum, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat
Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat
MODVIS Workshop
No abstract provided.
Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke
Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke
MODVIS Workshop
No abstract provided.
Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni
Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni
MODVIS Workshop
We report on preliminary results of an anatomically-inspired deep learning model of the visual system and its role in explaining the face inversion effect. Contrary to the generally accepted wisdom, our hypothesis is that the face inversion effect can be accounted for by the representation in V1 combined with the reliance on the configuration of features due to face expertise. We take two features of the primate visual system into account: 1) The foveated retina; and 2) The log-polar mapping from retina to V1. We simulate acquisition of faces, etc., by gradually increasing the number of identities the network learns. …
Feature Tracking And Geometrical Priors Counteract Illusory Non-Rigidities From Outputs Of Motion-Energy Cells, Akihito Maruya, Qasim Zaidi
Feature Tracking And Geometrical Priors Counteract Illusory Non-Rigidities From Outputs Of Motion-Energy Cells, Akihito Maruya, Qasim Zaidi
MODVIS Workshop
No abstract provided.
Perceived Object Motion Variance Across Optical Contexts, Jan Jaap R. Van Assen, Mitchell J.P. Van Zuijlen, Shin'ya Nishida
Perceived Object Motion Variance Across Optical Contexts, Jan Jaap R. Van Assen, Mitchell J.P. Van Zuijlen, Shin'ya Nishida
MODVIS Workshop
No abstract provided.
Modeling The Impacts Of Inter-Display And Inter-Lens Separation On Perceived Slant In Virtual Reality Head-Mounted Displays, Jonathan Tong, Laurie M. Wilcox, Robert S. Allison
Modeling The Impacts Of Inter-Display And Inter-Lens Separation On Perceived Slant In Virtual Reality Head-Mounted Displays, Jonathan Tong, Laurie M. Wilcox, Robert S. Allison
MODVIS Workshop
No abstract provided.
Fixational Eye Movements, Perceptual Filling-In, And Perceptual Fading Of Grayscale Images, Michael E. Rudd
Fixational Eye Movements, Perceptual Filling-In, And Perceptual Fading Of Grayscale Images, Michael E. Rudd
MODVIS Workshop
No abstract provided.
Constraining Computational Models Of Brightness Perception: What’S The Right Psychophysical Data?, Guillermo Aguilar, Joris Vincent, Marianne Maertens
Constraining Computational Models Of Brightness Perception: What’S The Right Psychophysical Data?, Guillermo Aguilar, Joris Vincent, Marianne Maertens
MODVIS Workshop
No abstract provided.
Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno
Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno
MODVIS Workshop
We concluded in our previous study that model cortical visual pathways actively retained information differently according to the different goals of the training tasks. One limitation of our study was that there was only one object in each input image whereas in reality there may be multiple objects in a scene. In our current study, we try to find a brain-like algorithm that can recognize and localize multiple objects.
Modeling Perceptual Grouping Strategies In Visual Search Tasks, Maria Kon, Gregory Francis
Modeling Perceptual Grouping Strategies In Visual Search Tasks, Maria Kon, Gregory Francis
MODVIS Workshop
No abstract provided.
Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos
Is The Selective Tuning Model Of Visual Attention Still Relevant?, John K. Tsotsos
MODVIS Workshop
No abstract provided.
The Fluid Representations Of Networks Estimating Liquid Viscosity, Jan Jaap R. Van Assen, Shin'ya Nishida, Roland W. Fleming
The Fluid Representations Of Networks Estimating Liquid Viscosity, Jan Jaap R. Van Assen, Shin'ya Nishida, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Selecting Maximally-Predictive Deep Features To Explain What Drives Fixations In Free-Viewing, Matthias Kümmerer, Thomas S.A. Wallis, Matthias Bethge
Selecting Maximally-Predictive Deep Features To Explain What Drives Fixations In Free-Viewing, Matthias Kümmerer, Thomas S.A. Wallis, Matthias Bethge
MODVIS Workshop
No abstract provided.
Modelling Human Perception Of High Gloss Materials Using Neural Networks, Konrad E. Prokott, Hideki Tamura, Roland W. Fleming
Modelling Human Perception Of High Gloss Materials Using Neural Networks, Konrad E. Prokott, Hideki Tamura, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
Differentiating Changes In Population Encoding Models With Psychophysics And Neuroimaging, Jason Hays, Fabian Soto Phd
MODVIS Workshop
It is now common among visual scientists to make inferences about neural population coding of stimuli from indirect measures such as those provided by neuroimaging and psychophysics. The success of such studies depends strongly on simulation work using standard population encoding models extended with decoders (in psychophysics) and measurement models (in neuroimaging). However, not all studies are accompanied by simulation work, and those that are tend to vary widely in their assumptions about encoding, decoding, and measurement. To solve these issues, we designed a Python package (PEMGUIN) to assist computational modelling by providing simple ways to manage encoders' tuning functions, …
Recovering Depth From Stereo Without Using Any Oculomotor Information, Tadamasa Sawada
Recovering Depth From Stereo Without Using Any Oculomotor Information, Tadamasa Sawada
MODVIS Workshop
The human visual system uses binocular disparity to perceive depth within 3D scenes. It is commonly assumed that the visual system needs oculomotor information about the relative orientation of the two eyes to perceive depth on the basis of binocular disparity. The necessary oculomotor information can be obtained from an efference copy of the oculomotor signals, or from a 2D distribution of the vertical disparity, specifically, from the vertical component of binocular disparity. It is known that oculomotor information from the efference copy and from the vertical disparity distribution can affect the perception of depth based on binocular disparity. But, …