Evidence map›Paper›PMID 33521029›Full record

ReviewFrontiers in nutrition2020

Estimating Dining Plate Size From an Egocentric Image Sequence Without a Fiducial Marker.

Wenyan Jia, Zekun Wu, Yiqiu Ren, Shunxin Cao, Zhi-Hong Mao, Mingui Sun

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Wenyan JiaDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
Zekun WuDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
Yiqiu RenDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
Shunxin CaoDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
Zhi-Hong MaoDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
Mingui SunDepartment of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
University of Pittsburgh · US

Funding

Automatic Recognition of Diet, Physical Activity and Sedentary Behavior Using a Smart Wearable DeviceR56DK113819 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SUN, MINGUI · 2018 to 2018
$490k
NIDDK NIH HHS R56 DK113819
6 · The paper itself

Abstract

Despite the extreme importance of food intake in human health, it is currently difficult to conduct an objective dietary assessment without individuals' self-report. In recent years, a passive method utilizing a wearable electronic device has emerged. This device acquires food images automatically during the eating process. These images are then analyzed to estimate intakes of calories and nutrients, assisted by advanced computational algorithms. Although this passive method is highly desirable, it has been thwarted by the requirement of a fiducial marker which must be present in the image for a scale reference. The importance of this scale reference is analogous to the importance of the scale bar in a map which determines distances or areas in any geological region covered by the map. Likewise, the sizes or volumes of arbitrary foods on a dining table covered by an image cannot be determined without the scale reference. Currently, the fiducial marker (often a checkerboard card) serves as the scale reference which must be present on the table before taking pictures, requiring human efforts to carry, place and retrieve the fiducial marker manually. In this work, we demonstrate that the fiducial marker can be eliminated if an individual's dining location is fixed and a one-time calibration using a circular plate of known size is performed. When the individual uses another circular plate of an unknown size, our algorithm estimates its radius using the range of pre-calibrated distances between the camera and the plate from which the desired scale reference is determined automatically. Our comparative experiment indicates that the mean absolute percentage error of the proposed estimation method is ~10.73%. Although this error is larger than that of the manual method of 6.68% using a fiducial marker on the table, the new method has a distinctive advantage of eliminating the manual procedure and automatically generating the scale reference.

Indexed as

dining plate sizeegocentric imagefiducial markertechnology-based dietary assessmentwearable device

Identifiers

PMID33521029
PMCPMC7840562
OpenAlexW3119942703

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.