Evidence map›Paper›PMID 40431963›Full record

ReviewSensors (Basel, Switzerland)2025

Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space.

Shuai Li, Shufang He, Yuanrui Dong, Caihong Dai, Jinyuan Liu, Yanfei Wang, Hiroaki Shigemasu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shuai LiDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.ORCID 0009-0002-0415-7753
Shufang HeDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.
Yuanrui DongDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.
Caihong DaiDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.
Jinyuan LiuDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.
Yanfei WangDivision of Optical Metrology, National Institute of Metrology, Beijing 100029, China.
Hiroaki ShigemasuSchool of Informatics, Kochi University of Technology, Kami City 782-8502, Kochi, Japan.ORCID 0000-0002-6156-0488

Funding

China Postdoctoral Science Foundation 2020M670412Fundamental Research Funds of National Institute of Metrology China AKYJJ2309Fundamental Research Funds of National Institute of Metrology China AKYZZ2215National Natural Science Foundation of China 62205323
6 · The paper itself

Abstract

BACKGROUND AND

objectivesDepth perception of the human visual system in three-dimensional (3D) space plays an important role in human-computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion parallax cues. This study aims to systemically summarize the related studies about depth perception specified by these two cues. MATERIALS AND

methodsWe conducted a literature investigation on related studies and summarized them from aspects like motivations, research trends, mechanisms, and interaction models of depth perception specified by these two cues.

resultsDevelopment trends show that depth perception research has gradually evolved from early studies based on a single cue to quantitative studies based on the interaction between these two cues. Mechanisms of these two cues reveal that depth perception specified by the binocular disparity cue is mainly influenced by factors like spatial variation in disparity, viewing distance, the position of visual field (or retinal image) used, and interaction with other cues; whereas that specified by the motion parallax cue is affected by head movement and retinal image motion, interaction with other cues, and the observer's age. By integrating these two cues, several types of models for depth perception are summarized: the weak fusion (WF) model, the modified weak fusion (MWF) model, the strong fusion (SF) model, and the intrinsic constraint (IC) model. The merits and limitations of each model are analyzed and compared.

conclusionsBased on this review, a clear picture of the study on depth perception specified by binocular disparity and motion parallax cues can be seen. Open research challenges and future directions are presented. In the future, it is necessary to explore methods for easier manipulating of depth cue signals in stereoscopic images and adopting deep learning-related methods to construct models and predict depths, to meet the increasing demand of human-computer interaction in complex 3D scenarios.

Indexed as

Depth PerceptionVision, BinocularVision DisparityArtificial IntelligenceCuesHumansMotionMotion Perception3D spacebinocular disparitydepth perceptionfusion modelshuman–computer interactionhuman visionmotion parallaxvirtual reality

Identifiers

PMID40431963
PMCPMC12115827

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.