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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.

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Related Experiment Video

Updated: Apr 3, 2026

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

Vanishing feature constraints calibration method for binocular vision sensor.

Zhenzhong Wei, Xiaokun Liu

|September 15, 2015

Summary

This summary is machine-generated.

A new flexible calibration method for binocular vision sensors uses a parallel line target. This efficient technique simplifies sensor calibration for improved accuracy in various applications.

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Last Updated: Apr 3, 2026

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Published on: March 3, 2023

Area of Science:

Computer Vision
Robotics
Metrology

Background:

Binocular vision sensors are crucial for 3D reconstruction and depth perception.
Accurate sensor calibration is essential for reliable performance.
Existing methods can be complex and time-consuming.

Purpose of the Study:

To develop a flexible and efficient calibration method for binocular vision sensors.
To improve the accuracy and convenience of sensor calibration.
To enable precise 3D measurements in various applications.

Main Methods:

Utilizing a planar target with parallel lines.
Employing vanishing feature and spacing constraints.
Combining linear methods for parameter separation and nonlinear optimization for global accuracy.

Main Results:

Achieved high accuracy of approximately 0.040mm at an 800mm working distance.
Demonstrated efficiency and convenience compared to existing toolboxes.
Validated precision through theoretical analysis, simulations, and real-world data.

Conclusions:

The proposed method offers a precise, efficient, and convenient solution for binocular vision sensor calibration.
Its simplicity makes it ideal for onsite and self-calibration scenarios.
This advancement facilitates more reliable 3D data acquisition in robotics and computer vision.