Evidence map›Paper›PMID 30626162›Full record

ArticleSensors (Basel, Switzerland)2019

Implicit Calibration Using Probable Fixation Targets.

Pawel Kasprowski, Katarzyna Harezlak, Przemysław Skurowski

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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

3 authors.

Pawel KasprowskiInstitute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland. pawel.kasprowski@polsl.pl.ORCID 0000-0002-2090-335X
Katarzyna HarezlakInstitute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland. katarzyna.harezlak@polsl.pl.ORCID 0000-0003-3573-9772
Przemysław SkurowskiInstitute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland. przemyslaw.skurowski@polsl.pl.ORCID 0000-0001-5306-9528

Funding

Silesian University of Technology 02/010/RGH18/0131
6 · The paper itself

Abstract

Proper calibration of eye movement signal registered by an eye tracker seems to be one of the main challenges in popularizing eye trackers as yet another user-input device. Classic calibration methods taking time and imposing unnatural behavior on eyes must be replaced by intelligent methods that are able to calibrate the signal without conscious cooperation by the user. Such an implicit calibration requires some knowledge about the stimulus a user is looking at and takes into account this information to predict probable gaze targets. This paper describes a possible method to perform implicit calibration: it starts with finding probable fixation targets (PFTs), then it uses these targets to build a mapping-probable gaze path. Various algorithms that may be used for finding PFTs and mappings are presented in the paper and errors are calculated using two datasets registered with two different types of eye trackers. The results show that although for now the implicit calibration provides results worse than the classic one, it may be comparable with it and sufficient for some applications.

Indexed as

calibrationeye movementeye trackingoptimization

Identifiers

PMID30626162
PMCPMC6339230

What OpenQuestion holds

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Registered trials

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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.