Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Shape and Texture of Coarse Aggregate01:25

Shape and Texture of Coarse Aggregate

1.3K
Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...
1.3K
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

1.8K
Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
1.8K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

855
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
855
Topographic Surveying and Contours01:29

Topographic Surveying and Contours

1.6K
Topographic surveying is critical for documenting the Earth's surface, focusing on capturing elevations, slopes, and natural and man-made features. It is essential in construction planning, water resource management, and land-use analysis. The primary outcome of such surveys is a topographic map, which uses contour lines to visually represent the shape and slope of the terrain, providing valuable insights into the landscape's characteristics.Contour lines are fundamental to understanding the...
1.6K
Second Derivatives and the Shape of a Graph01:29

Second Derivatives and the Shape of a Graph

326
The second derivative of a function provides essential information about a graph's curvature and how it changes over an interval. It helps determine whether a function is concave upward or concave downward and identifies points where the curvature changes. These properties are fundamental in analyzing real-world scenarios, such as changes in road elevation, population growth, and economic trends.A function f(x) is considered concave upward on an interval if its graph lies above all its tangent...
326
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

482
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
482

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Interleaved periods of exercise do not enhance visual perceptual learning.

Journal of vision·2025
Same author

Exploring the Phenotype and Possible Mechanisms of Palinopsia in Visual Snow Syndrome.

Investigative ophthalmology & visual science·2024
Same author

Efficacy of perceptual learning in low vision: A systematic review and meta-analysis.

Optometry and vision science : official publication of the American Academy of Optometry·2024
Same author

Improving Understanding of Visual Snow by Quantifying its Appearance and Effect on Vision.

Investigative ophthalmology & visual science·2024
Same author

Continuous psychophysics for two-variable experiments; A new "Bayesian participant" approach.

i-Perception·2024
Same author

Target motion misjudgments reflect a misperception of the background; revealed using continuous psychophysics.

i-Perception·2024

Related Experiment Video

Updated: May 4, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.6K

Detecting shape change: characterizing the interaction between texture-defined and contour-defined borders.

Ken W S Tan1, J Edwin Dickinson, David R Badcock

  • 1The University of Western Australia, School of Psychology, Crawley, Western Australia, Australia.

Journal of Vision
|December 18, 2013
PubMed
Summary
This summary is machine-generated.

The human visual system processes shapes globally, whether defined by explicit paths or texture borders. However, different visual cues for shape are not integrated for discrimination, suggesting separate processing pathways.

Keywords:
RF patternsShapeformglobal poolingtexture segmentation

More Related Videos

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.1K
Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

8.7K

Related Experiment Videos

Last Updated: May 4, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.6K
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.1K
Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

8.7K

Area of Science:

  • Visual Perception
  • Computational Neuroscience
  • Cognitive Psychology

Background:

  • Human visual system exhibits high sensitivity to shape changes, often due to global pooling of local information.
  • Previous research confirmed global pooling for contiguous element shapes but not for texture-defined shapes.
  • Texture and luminance cues are integrated for shape detection, but their role in shape discrimination remains unclear.

Purpose of the Study:

  • To investigate whether global pooling applies to shapes defined by texture-segmentation borders.
  • To determine if texture and luminance cues are integrated for shape discrimination, not just detection.

Main Methods:

  • Utilized controlled shapes defined by explicit Gabor paths, texture-segmentation borders, or a combination of both cues.
  • Assessed shape processing by analyzing detection thresholds for the different stimulus types.

Main Results:

  • All tested stimuli, regardless of cue type, were processed globally by the visual system.
  • Shape discrimination thresholds for combined cues aligned with predictions from an independent-cue vector sum model.
  • No evidence of integration across different shape cues (texture vs. luminance) was found for discrimination.

Conclusions:

  • Local elements are integrated within contours and processed by global shape-detection mechanisms.
  • Despite global processing of individual cues, integration does not occur across distinct shape cues for discrimination.
  • Suggests separate neural mechanisms for processing different types of visual shape information.