Evidence map›Paper›PMID 24326674›Full record

ArticleJournal of visualized experiments : JoVE2013

High-resolution, high-speed, three-dimensional video imaging with digital fringe projection techniques.

Laura Ekstrand, Nikolaus Karpinsky, Yajun Wang, Song Zhang

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Laura Ekstrand3D Machine Vision Laboratory, Department of Mechanical Engineering, Iowa State University.
Nikolaus Karpinsky
Yajun Wang
Song Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces. Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth. However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras(1). The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera's field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation. Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop. DFP systems can also achieve the same measurement resolution as the camera. For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in(1-5)). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30 Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame(6,7). Binary defocusing DFP methods can achieve even greater speeds(8). Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis(9), facial animation(10), cardiac mechanics studies(11), and fluid surface measurements, but many other potential applications exist. This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.

Indexed as

Facial ExpressionFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalVideo Recording

Identifiers

PMID24326674
PMCPMC4028810

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.