Evidence map›Paper›PMID 32466283›Full record

ReviewSensors (Basel, Switzerland)2020

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems.

Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 9% of its field
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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. A Survey of Museum Applied Research Based on Mobile Augmented Reality.Computational intelligence and neuroscience · 2022
    Review
  7. Article
  8. 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

2 authors at 1 institution in 2 countries.

Abolghasem Sadeghi-NiarakiGeoinformation Tech. Center of Excellence, Faculty of Geodesy& Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19697, Iran.ORCID 0000-0002-0048-8216
Soo-Mi ChoiDepartment of Computer Science and Engineering, Sejong University, Seoul 143-747, Korea.ORCID 0000-0002-6710-1434
Sejong University · KR

Funding

the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) IITP-2019-2016-0-00312
6 · The paper itself

Abstract

Most existing augmented reality (AR) applications are suitable for cases in which only a small number of real world entities are involved, such as superimposing a character on a single surface. In this case, we only need to calculate pose of the camera relative to that surface. However, when an AR health or environmental application involves a one-to-one relationship between an entity in the real-world and the corresponding object in the computer model (geo-referenced object), we need to estimate the pose of the camera in reference to a common coordinate system for better geo-referenced object registration in the real-world. New innovations in developing cheap sensors, computer vision techniques, machine learning, and computing power have helped to develop applications with more precise matching between a real world and a virtual content. AR Tracking techniques can be divided into two subcategories: marker-based and marker-less approaches. This paper provides a comprehensive overview of marker-less registration and tracking techniques and reviews their most important categories in the context of ubiquitous Geospatial Information Systems (GIS) and AR focusing to health and environmental applications. Basic ideas, advantages, and disadvantages, as well as challenges, are discussed for each subcategory of tracking and registration techniques. We need precise enough virtual models of the environment for both calibrations of tracking and visualization. Ubiquitous GISs can play an important role in developing AR in terms of providing seamless and precise spatial data for outdoor (e.g., environmental applications) and indoor (e.g., health applications) environments.

Indexed as

Augmented RealityImaging, Three-DimensionalInformation SystemsComputer SimulationUser-Computer Interfaceaugmented realitycamera pose estimation and registrationenvironmental applicationshealth &amptrackingubiquitous geospatial information systems

Identifiers

PMID32466283
PMCPMC7285507
OpenAlexW3026156313

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.