Evidence map›Paper›PMID 38020432›Full record

ArticleData in brief2023

Data2MV - A user behaviour dataset for multi-view scenarios.

Tiago Soares da Costa, Maria Teresa Andrade, Paula Viana, Nuno Castro Silva

Abstract read
In one paragraph

Article in Data in brief, 2023. 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.

Tiago Soares da CostaCentre for Telecommunications and Multimedia, INESC TEC, Porto, Portugal.
Maria Teresa AndradeFaculty of Engineering, University of Porto, Porto, Portugal.
Paula VianaSchool of Engineering, ISEP, Polytechnic of Porto, Porto, Portugal.
Nuno Castro SilvaFaculty of Engineering, University of Porto, Porto, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Data2MV dataset contains gaze fixation data obtained through experimental procedures from a total of 45 participants using an Intel RealSense F200 camera module and seven different video playlists. Each of the playlists had an approximate duration of 20 minutes and was viewed at least 17 times, with raw tracking data being recorded with a 0.05 second interval. The Data2MV dataset encompasses a total of 1.000.845 gaze fixations, gathered across a total of 128 experiments. It is also composed of 68.393 image frames, extracted from each of the 6 videos selected for these experiments, and an equal quantity of saliency maps, generated from aggregate fixation data. Software tools to obtain saliency maps and generate complementary plots are also provided as an open-source software package. The Data2MV dataset was publicly released to the research community on Mendeley Data and constitutes an important contribution to reduce the current scarcity of such data, particularly in immersive, multi-view streaming scenarios.

Indexed as

Adaptive streamingDeep learningHead-trackingMultimediaMulti-viewView prediction

Identifiers

PMID38020432
PMCPMC10630600

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.