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Related Concept Videos

Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
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.
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category, whereas...
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

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...
Factors Affecting Perception01:25

Factors Affecting Perception

Perception is influenced by perceptual set, context, motivation, and emotion. Perceptual set, or perceptual expectancy, refers to the tendency to perceive things in a particular way, influenced by previous experiences and expectations. This phenomenon affects the interpretation of stimuli, creating a set of mental tendencies and assumptions that impact sensory perceptions of sound, taste, touch, and sight.
An illustrative example of a perceptual set is the scenario where an airline pilot told...
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.

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Related Experiment Video

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Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Computational color constancy: survey and experiments.

Arjan Gijsenij1, Theo Gevers, Joost van de Weijer

  • 1University of Amsterdam, Amsterdam 1098 XG, The Netherlands. a.gijsenij@uva.nl

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 24, 2011
PubMed
Summary
This summary is machine-generated.

This survey reviews computational color constancy methods for computer vision. It categorizes algorithms and evaluates state-of-the-art techniques on standard datasets.

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Area of Science:

  • Computer Vision
  • Image Processing

Background:

  • Computational color constancy is essential for reliable computer vision.
  • Accurate color perception in images under varying illumination is a key challenge.

Purpose of the Study:

  • To provide a comprehensive survey of recent computational color constancy methods.
  • To establish criteria for assessing color constancy algorithms.
  • To propose a taxonomy for existing algorithms.

Main Methods:

  • Categorization of algorithms into static, gamut-based, and learning-based methods.
  • Discussion of experimental setups and publicly available datasets.
  • Evaluation of freely available state-of-the-art methods on two datasets.

Main Results:

  • A structured taxonomy of computational color constancy algorithms.
  • Comparative evaluation of various methods on benchmark datasets.
  • Identification of effective state-of-the-art approaches.

Conclusions:

  • The survey provides a structured overview and assessment of computational color constancy.
  • Evaluations highlight the performance of different algorithmic approaches.
  • This work serves as a guide for researchers and practitioners in the field.