DisCaaS: Micro Behavior Analysis on Discussion by Camera as a Sensor.

Ko Watanabe, Yusuke Soneda, Yuki Matsuda, Yugo Nakamura, Yutaka Arakawa, Andreas Dengel, Shoya Ishimaru

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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.

Enhancing 360 Video Streaming through Salient Content in Head-Mounted Displays.Sensors (Basel, Switzerland) · 2023
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

7 authors.

Ko WatanabeDepartment of Computer Science, University of Kaiserslautern & DFKI GmbH, 67663 Kaiserslautern, Germany.ORCID 0000-0003-0252-1785

Yusuke SonedaGraduate School of Science and Technology, Nara Institute of Science and Technology, Nara 630-0192, Japan.

Yuki MatsudaGraduate School of Science and Technology, Nara Institute of Science and Technology, Nara 630-0192, Japan.ORCID 0000-0002-3135-4915

Yugo NakamuraDepartment of Information Science and Technology, Graduate School and Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.ORCID 0000-0002-8834-5323

Yutaka ArakawaDepartment of Information Science and Technology, Graduate School and Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.ORCID 0000-0002-7156-9160

Andreas DengelDepartment of Computer Science, University of Kaiserslautern & DFKI GmbH, 67663 Kaiserslautern, Germany.

Shoya IshimaruDepartment of Computer Science, University of Kaiserslautern & DFKI GmbH, 67663 Kaiserslautern, Germany.ORCID 0000-0002-5374-1510

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of various types of commercial cameras (compact, high resolution, high angle of view, high speed, and high dynamic range, etc.) has contributed significantly to the understanding of human activities. By taking advantage of the characteristic of a high angle of view, this paper demonstrates a system that recognizes micro-behaviors and a small group discussion with a single 360 degree camera towards quantified meeting analysis. We propose a method that recognizes

Indexed as

Human ActivitiesPhotographyCOVID-19HumansPandemics3D pose estimationcamera as a smart sensordigital camerahuman action recognitionmeeting analysisRGB sensors

Identifiers

PMID34502609

DOI10.3390/s21175719

PMCPMC8434061

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.