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ZENODO
Dataset . 2018
License: CC BY NC ND
Data sources: Datacite
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ZENODO
Dataset . 2018
License: CC BY NC ND
Data sources: ZENODO
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ZENODO
Dataset . 2018
License: CC BY NC ND
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY NC ND
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY NC ND
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2018
License: CC BY NC ND
Data sources: Sygma
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Mocap Gait Motion Samples - Optical Marker Tajectories

Authors: Jiménez Bascones, Juan Luis; Graña Romay, Manuel;

Mocap Gait Motion Samples - Optical Marker Tajectories

Abstract

======================= Summary ======================= This database gathers a set of optical marker-based motion capture (mocap) tracking samples. Each sample corresponds to a single acquisition containing the 3D trajectories of a set of markers along a continuous interval of time. Keywords: Motion capture, mocap, Gait analysis, marker tracking. ======================= Data description ======================= Several persons wearing small reflective balls (markers) were asked to walk normally while recorded using motion capture cameras. These cameras, previously calibrated, are thought to detect the 2D pixel image position of the markers against the background thanks to IR lightning they are provided with. The XYZ position can be afterwards recovered by means of photogrammetric methods, whereas the tracking is kept across the frames. This data set contains the raw 3D trajectories of the aforementioned markers along the time. The set of markers is the layout proposed by Kadaba, Ramakrishnan, and Wootten, from the Helen Hayes Hospital. More details can be found in 'Dynamics of Human Gait' from Vaughan et al. Check out 'HH_marker_arrangement.png' for a visual description on marker placement. This database was built on purpose to serve as ground truth for the doctoral research "Cloud Point Labeling in Optical Motion Capture Systems", written by Juan L. Jiménez B. and supervised by Prof. Manuel Graña, from the Computational Intelligence Group, University of the Basque Country (UPV/EHU), and expected to be presented by the beginning of 2019. This work has been partially supported by the EC through project CybSPEED funded by the H2020 MSCA-RISE grant agreement Num. 777720. ======================= Equipment ======================= The following elements were taken to harvest the data: - Six (6) motion capture cameras model S250e from Natural Point Inc. ( https://optitrack.com/ ); - Fifteen (15) passive-reflective optical markers; - One computer running motion capture software from s.t.t.; - A number of other minor accessories as camera wall mounts, Ethernet wires, adhesive tape, coffee and time. ======================= Technical details ======================= Database size: 71 recordings between 1.5 and 7 seconds long, summing up more than 20.000 frames Exercise: regular gait motion at different paces People: 14 different persons of different ages and shapes were recorded. No gait pathologies openly acknowledged. Number of markers: 15 (Helen Hayes marker system) Native camera resolution: 800x800 pixels Sampling frequency: 100Hz Cartesian units: millimeters Right handed reference frame, +Y vertical upwards, ground height at Y=~0 ======================= Data base format ======================= The database is composed by 71 different files, one per gait sequence. Each file is written in plain ASCII, comma separated values (CSV) format. Each line represents an instant of time (frame) containing the 3D Cartesian positions of all the 15 markers with to 2 mantissa digits and dot symbol as decimal separator. A triple 'nan nan nan' instead of actual numbers stands for marker occlusion and consequently no measured position can be given. The coordinates are numerically arranged as follows: X1; Y1; Z1; X2; Y2; Z2; ... Xi; Yi; Zi; ... X15; Y15; Z15; ... where 'i' refers to the i-th marker among the following list: 1- Right ASIS 2- Left ASIS 3- Sacrum 4- Right Femoral wand 5- Left Femoral wand 6- Right Femoral epicondyle 7- Left Femoral epicondyle 8- Right Tibial wand 9- Left Tibial wand 10- Right Malleolus 11- Left Malleolus 12- Right Heel 13- Left Heel 14- Right Metatarsal head II 15- Left Metatarsal head II ======================= Privacy statement ======================= The personal privacy of the volunteers, adults of 25 and over, remains protected since no confidential data has been collected at any time. ======================= Further information ======================= If you find any mistake or experience any trouble in the interpretation of the data, please do not hesitate to contact us.

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Keywords

Motion capture, mocap, motion gait analysis, marker tracking

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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