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Size-Dictionary Interpolation for Robot’s Adjustment

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, May 2015
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Title
Size-Dictionary Interpolation for Robot’s Adjustment
Published in
Frontiers in Bioengineering and Biotechnology, May 2015
DOI 10.3389/fbioe.2015.00063
Pubmed ID
Authors

Morteza Daneshmand, Alvo Aabloo, Gholamreza Anbarjafari

Abstract

This paper describes the classification and size-dictionary interpolation of the three-dimensional data obtained by a laser scanner to be used in a realistic virtual fitting room, where automatic activation of the chosen mannequin robot, while several mannequin robots of different genders and sizes are simultaneously connected to the same computer, is also considered to make it mimic the body shapes and sizes instantly. The classification process consists of two layers, dealing, respectively, with gender and size. The interpolation procedure tries to find out which set of the positions of the biologically inspired actuators for activation of the mannequin robots could lead to the closest possible resemblance of the shape of the body of the person having been scanned, through linearly mapping the distances between the subsequent size-templates and the corresponding position set of the bioengineered actuators, and subsequently, calculating the control measures that could maintain the same distance proportions, where minimizing the Euclidean distance between the size-dictionary template vectors and that of the desired body sizes determines the mathematical description. In this research work, the experimental results of the implementation of the proposed method on Fits.me's mannequin robots are visually illustrated, and explanation of the remaining steps toward completion of the whole realistic online fitting package is provided.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 17%
Professor > Associate Professor 1 17%
Researcher 1 17%
Student > Doctoral Student 1 17%
Unknown 2 33%
Readers by discipline Count As %
Computer Science 1 17%
Materials Science 1 17%
Engineering 1 17%
Unknown 3 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 May 2015.
All research outputs
#18,410,971
of 22,805,349 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,389
of 6,525 outputs
Outputs of similar age
#192,595
of 266,320 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#33
of 53 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,525 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,320 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.