Evidence map›Paper›PMID 35591022›Full record

ArticleSensors (Basel, Switzerland)2022

A Comparison and Evaluation of Stereo Matching on Active Stereo Images.

Mingyu Jang, Hyunse Yoon, Seongmin Lee, Jiwoo Kang, Sanghoon Lee

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

5 authors.

Mingyu JangDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.
Hyunse YoonDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.
Seongmin LeeDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.ORCID 0000-0002-1564-5077
Jiwoo KangDepartment of IT Engineering, Sookmyung Women's University, Seoul 04310, Korea.ORCID 0000-0001-7622-0817
Sanghoon LeeDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea.ORCID 0000-0001-9895-5347

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relationship between the disparity and depth information of corresponding pixels is inversely proportional. Thus, in order to accurately estimate depth from stereo vision, it is important to obtain accurate disparity maps, which encode the difference between horizontal coordinates of corresponding image points. Stereo vision can be classified as either passive or active. Active stereo vision generates pattern texture, which passive stereo vision does not have, on the image to fill the textureless regions. In passive stereo vision, many surveys have discovered that disparity accuracy is heavily reliant on attributes, such as radiometric variation and color variation, and have found the best-performing conditions. However, in active stereo matching, the accuracy of the disparity map is influenced not only by those affecting the passive stereo technique, but also by the attributes of the generated pattern textures. Therefore, in this paper, we analyze and evaluate the relationship between the performance of the active stereo technique and the attributes of pattern texture. When evaluating, experiments are conducted under various settings, such as changing the

Indexed as

AlgorithmsImaging, Three-DimensionalVision, Ocularactive stereo matchingdisparity accuracyinfrared imagematching costoff-the-shelf active stereo sensorperformance evaluation

Identifiers

PMID35591022
PMCPMC9100404

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.