Social and Behavioral Sciences Commons^™

Housing Diversity In Children’S Literature, Carla Earhart

Charleston Library Conference

Previous studies have examined diversity in children’s literature: Gender diversity, racial diversity, religious diversity, and diversity in family composition. This project examines an often overlooked diversity issue in children’s literature: Housing diversity. In the stories they read and the accompanying images, children need to see a variety of housing environments and need to see the settings and the people portrayed in a positive manner.

Renting an apartment is an increasingly popular housing option for many families. However, many children’s books glamorize living in a traditional house. Using a rubric designed by the course instructor, students in a university immersive learning …

Determining Visual Shape Features For Novel Object Classes, Yaniv Morgenstern, Filipp Schmidt, Roland W. Fleming

MODVIS Workshop

The visual representation of shape reduces a high-dimensional input into a smaller set of more informative features. These features can span a range of abstractions from shallow features based on statistical summaries of images, to deep features related to the generative causes of the shapes. Here we examined the depth of the visual system’s representation of shape by comparing human judgments of whether novel shapes appeared to belong to a common class with a range of models with different shape representations. Each shape class was based on a unique 2D base shape, formed by attaching parts of contours from different …

Shape Features Underlying The Perception Of Liquids, Jan Jaap R. Van Assen, Pascal Barla, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Real Time Learning Level Assessment Using Eye Tracking, Saurin S. Parikh, Hari Kalva

MODVIS Workshop

E-Learning is emerging as a convenient and effective learning tool. However, the challenge with eLearning is the lack of effective tools to assess levels of learning. Ability to predict difficult content in real time enables eLearning systems to dynamically provide supplementary content to meet learners’ needs. Recent developments have made possible low-cost eye trackers, which enables a new class of applications based on eye response. In comparison to past attempts using bio-metrics in learning assessments, with eye tracking, we can have access to the exact stimulus that is causing the response. A key aspect of the proposed approach is the …

Neural Computation Of Statistical Image Properties In Peripheral Vision, Christoph Zetzsche, Ruth Rosenholtz, Noshaba Cheema, Konrad Gadzicki, Lex Fridman

MODVIS Workshop

No abstract provided.

The Role Of Symmetry In Scene Categorization By Human Observers, John D. Wilder, Morteza Rezanejad, Sven Dickinson, Allan Jepson, Kaleem Siddiqi, Dirk B. Walther

MODVIS Workshop

No abstract provided.

Using Classification Images To Understand Models Of Lightness Perception, Minjung Kim, Jason M. Gold, Richard F. Murray

MODVIS Workshop

No abstract provided.

Edge Integration And Image Segmentation In Lightness And Color: Computational And Neural Theory, Michael E. Rudd

MODVIS Workshop

No abstract provided.

Positive Or Correlated Channels In Parallel Race Systems: Help Or Hurt?, James T. Townsend, Ru Zhang, Yanjun Liu, Michael J. Wenger

MODVIS Workshop

No abstract provided.

Color Algebras, Jeffrey B. Mulligan

MODVIS Workshop

No abstract provided.

Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre

MODVIS Workshop

A central goal in vision science is to identify features that are important for object and scene recognition. Reverse correlation methods have been used to uncover features important for recognizing faces and other stimuli with low intra-class variability. However, these methods are less successful when applied to natural scenes with variability in their appearance.

To rectify this, we developed Clicktionary, a web-based game for identifying features for recognizing real-world objects. Pairs of participants play together in different roles to identify objects: A “teacher” reveals image regions diagnostic of the object’s category while a “student” tries to recognize the object. Aggregating …

A Computational Account Of A Class Of Orientation Illusions, Dejan M. Todorovic

MODVIS Workshop

Contrast-dependent orientation illusions are phenomena in which the appearance of the illusion depends not only on geometrical arrangements of the constituents of illusory configurations, but also on their luminance levels. Whereas certain standard configurations may evoke strong illusory effects, their contrast-manipulated variants (configurations in which only the luminance contrast polarity of some of their elements is manipulated, while retaining the geometry of the standard versions) may show weakened or no illusory effects, or even reversed illusions. Although generally rather salient, the contrast-dependent illusions have not been researched in much detail, except for the well-known Münsterberg (Café Wall) illusion. Here I …

Heuristics From Statistics—Modeling The Behavior And Perception Of Non-Rigid Materials, Vivian C. Paulun, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Modeling The Neural Circuitry Underlying The Behavioral And Eeg Correlates Of Attentional Capture, Chloe Callahan-Flintoft, Brad Wyble

MODVIS Workshop

The Reactive-Convergent Gradient Field model (R-CGF) is a unique approach to modeling spatial attention in that it links neural mechanisms to event related potentials (ERPs) from scalp EEG. This model was developed with the aim of explaining different, sometimes conflicting, findings in the attention literature. Specifically, this model address conflicting findings showing both simultaneous and serial deployment of attention. Another argument addressed by the model is whether attention to a location invokes a suppression of the spatial surround, or the selective inhibition of distractors. With the R-CGF, we have found that these results are not as incompatible as they appear …

Spatial-Temporal Visible Contrast Energy Predictions Of Detection Thresholds, Albert Ahumada, Andrew B. Watson, Jihyun Yeonan-Kim

MODVIS Workshop

The Barten (1994) spatial-temporal model was used to predict the Gabor stimulus contrast energy thresholds reported by Carney et al. (2013). The RMS error of fit was 1.6 dB, corrected for the number of parameters (6) estimated. The model has two lowpass spatial-temporal channels, combined by inhibition as in our spatial models (Watson & Ahumada, 2005; Ahumada & Watson, 2013). Computation of models predictions were greatly simplified by the spatial-temporal separability of the stimuli and the simplifications that result from using Gaussian filters in the spatial domain. The best fitting spatial filter frequency cutoffs are 11.4 and 0.88 cpd. The …

Computational Modeling Of Contrast Sensitivity And Orientation Tuning In Schizophrenia, Steven M. Silverstein, Docia L. Demmin, James A. Bednar

MODVIS Workshop

Computational modeling is being increasingly used to understand schizophrenia, but, to date, it has not been used to account for the common perceptual disturbances in the disorder. We manipulated schizophrenia-relevant parameters in the GCAL (gain control, adaptation, laterally connected) model (Stevens et al., 2013), run using the Topographica simulator (Bednar, 2012), to model low-level visual processing changes in the disorder. Our models incorporated: separate sheets for retinal, LGN, and V1 activity; gain control in the LGN; homeostatic adaptation in V1 based on a weighted sum of all inputs and limited by a logistic (sigmoid) nonlinearity; lateral excitation and inhibition in …