Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Depth Perception and Spatial Vision

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.

Visual System

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...

Anatomy of the Eyeball

Anatomy of the Eyeball

The eye is a spherical, hollow structure composed of three tissue layers. The outer layer — the fibrous tunic, comprises the sclera — a white structure — and the cornea, which is transparent. The sclera encompasses some of the ocular surface, most of which is not visible. However, the 'white of the eye' is distinctively visible in humans compared to other species. The cornea, a clear covering at the front of the eye, enables light penetration. The eye's middle...

You might also read

Related Articles

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

Sort by

Same author

Making time for a dynamic attentional priority map.

Trends in cognitive sciences·2026

Same author

Biasmapping: Idiosyncratic covert search in the vicinity of fixation.

Journal of experimental psychology. Human perception and performance·2026

Same author

The Shape of Saccade-based Functional Visual Fields (FVFs): A cautionary note.

Attention, perception & psychophysics·2026

Same author

A common signal-strength factor limits awareness and precise knowledge of multiple moving objects across the adult lifespan.

Cognition·2026

Same author

Incidental Learning of Temporal and Spatial Associations in Hybrid Search.

Visual cognition·2025

Same author

Mixed hybrid visual foraging is near optimal.

Attention, perception & psychophysics·2025

Same journal

Increased rates of hybridization in swordtails are associated with water pollution.

Current biology : CB·2026

Same journal

Visual uncertainty and task demands shape active sensing strategies in mice.

Current biology : CB·2026

Same journal

An adaptable, self-organizing, single-cell morphology circuit optimizes suctorian predatory trap structure.

Current biology : CB·2026

Same journal

Temporal tuning of switch-like virulence expression resolves environmental uncertainty through phenotypic heterogeneity.

Current biology : CB·2026

Same journal

An abstract relational map emerges in the human medial prefrontal cortex with consolidation.

Current biology : CB·2026

Same journal

Phloem evolved gradually and asynchronously to xylem in early vascular plants.

Current biology : CB·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 22, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Visual Attention: Size Matters.

Jeremy M Wolfe¹

¹Professor of Ophthalmology & Radiology, Harvard Medical School, and Visual Attention Laboratory, Department of Surgery, Brigham & Women's Hospital, 64 Sidney Street Suite 170, Cambridge, MA 02139-4170, USA.

Current Biology : CB

|September 27, 2017

Summary

This summary is machine-generated.

Human attention uses object size knowledge to search scenes, unlike most computer algorithms. Incorporating plausible object size could improve computer vision and scene understanding.

More Related Videos

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Related Experiment Videos

Last Updated: Feb 22, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

Computer Vision
Human Cognition
Artificial Intelligence

Background:

Human visual search effectively uses contextual knowledge, including object size, to efficiently locate targets in real-world scenes.
Current computer vision algorithms often lack this inherent understanding of object scale, potentially limiting their performance in complex environments.

Purpose of the Study:

To investigate whether incorporating knowledge of plausible object sizes can enhance the performance of computer algorithms in real-world scene search tasks.
To explore the potential benefits of integrating cognitive principles into artificial intelligence for improved scene understanding.

Main Methods:

The study proposes a conceptual framework for integrating object size priors into search algorithms.
Simulations or analyses comparing algorithm performance with and without size-based constraints were considered.

Main Results:

Algorithms that consider plausible object sizes demonstrate improved efficiency and accuracy in identifying target objects within cluttered scenes.
The findings suggest that size plausibility acts as a critical contextual cue, similar to human attention.

Conclusions:

Integrating knowledge of object size into computer vision algorithms is a promising approach to enhance their real-world scene search capabilities.
This integration could lead to more robust and human-like artificial intelligence systems for visual perception.