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Related Concept Videos

Vision01:24

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
Velocity and Position by Graphical Method01:34

Velocity and Position by Graphical Method

Velocity and position can be calculated from the known function of acceleration as a function of time. The total area under the acceleration-time graph and the velocity-time graph gives the change in velocity and position, respectively. In the case of an airplane, its acceleration is tracked using the inertial navigation system. The pilot provides the input of the airplane's initial position and velocity before takeoff. The inertial navigation system then uses the acceleration data to calculate...
Color Vision01:24

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
Visual Agnosia01:12

Visual Agnosia

Visual agnosia is a condition characterized by the inability to recognize visually presented objects despite having normal vision. For instance, a person with visual agnosia can describe the shape and color of an object but cannot identify or name it. This impairment does not affect their visual field, acuity, color vision, brightness discrimination, language, or memory. An example of this condition in a social setting is someone at a dinner party asking for "that silver thing with a round end"...

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Related Experiment Video

Updated: Jun 28, 2026

VisualEyes: A Modular Software System for Oculomotor Experimentation
10:41

VisualEyes: A Modular Software System for Oculomotor Experimentation

Published on: March 25, 2011

Viz-A-Vis: toward visualizing video through computer vision.

Mario Romero1, Jay Summet, John Stasko

  • 1Georgia Tech. mromero@cc.gatech.edu

IEEE Transactions on Visualization and Computer Graphics
|November 8, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces Viz-A-Vis, a system using computer vision to aid video data transforms for activity analysis. It supports human analysts by automating low-level perception tasks in overhead video data.

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Related Experiment Videos

Last Updated: Jun 28, 2026

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Published on: January 15, 2018

Area of Science:

  • Computer Vision
  • Information Visualization
  • Human-Computer Interaction

Background:

  • Traditional information visualization relies on manual data transformation.
  • Analyzing large volumes of video data for activity analysis is challenging.
  • Automatic video analysis is an ongoing research problem in computer vision.

Purpose of the Study:

  • To propose integrating low-level computer vision with human analysis for video data transforms.
  • To present Viz-A-Vis, an overhead video system for activity analysis.
  • To address challenges in analyzing large-scale overhead video data.

Main Methods:

  • Developing computer vision techniques to support data transforms for video.
  • Implementing Viz-A-Vis, an overhead video capture and access system.
  • Focusing on automating low-level perception tasks in video analysis.

Main Results:

  • Viz-A-Vis facilitates activity analysis from overhead video.
  • The system aims to make large video datasets more manageable for analysts.
  • Initial steps are presented to address challenges in video data volume and analysis.

Conclusions:

  • Computer vision can significantly enhance the data transformation process in information visualization for video.
  • Viz-A-Vis demonstrates a hybrid approach where computers handle perception and humans handle reasoning.
  • Further research in automatic video analysis is crucial for advancing this field.