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The Use of Collision Detection to Infer Multi-Camera Calibration Quality

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, May 2015
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Title
The Use of Collision Detection to Infer Multi-Camera Calibration Quality
Published in
Frontiers in Bioengineering and Biotechnology, May 2015
DOI 10.3389/fbioe.2015.00065
Pubmed ID
Authors

Sook-Yee Chong, Beate Dorow, Ellankavi Ramasamy, Florian Dennerlein, Oliver Röhrle

Abstract

Optical motion capture systems are widely used in sports and medicine. The performance of these systems depends on, amongst other factors, the quality of the camera calibration process. This study proposes a technique to assess the accuracy of the extrinsic camera parameters, as estimated during calibration. This method relies on the fact that solid objects in the real world cannot possess a gap in between, nor interpenetrate, when in contact with each other. In our study, we used motion capture to track successive collisions of two solid moving objects. The motion of solid objects was simulated based on trajectories measured by a multi-camera system and geometric information acquired from computed tomography. The simulations were then used to determine the amount of overlap or gap between them. This technique also takes into account errors resulting from markers moving close to one another, and better replicates actual movements during motion capture. We propose that this technique of successively colliding two solid moving objects may provide a means of measuring calibration accuracy.

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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 %
Student > Ph. D. Student 2 33%
Researcher 2 33%
Student > Master 1 17%
Unknown 1 17%
Readers by discipline Count As %
Engineering 2 33%
Mathematics 1 17%
Sports and Recreations 1 17%
Design 1 17%
Unknown 1 17%
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 12 May 2015.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#4,052
of 8,501 outputs
Outputs of similar age
#205,989
of 279,139 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#33
of 54 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,501 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 37th percentile – i.e., 37% 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 279,139 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 54 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.