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Daily Life Activities Dataset

<p><strong>Experiment design</strong></p> <p>The Daily Life Activities (DLA) dataset consists of trials of daily life object manipulation tasks performed by a human. The dataset consists of ten tasks: <em>cutting, painting, pouring with cup, putting cup away, quarter turn, scooping and pouring, scooping food, shaking, sinusoidal motion</em>, and <em>table wiping</em>. In this dataset, a high variation in the context was purposefully introduced. That is, the tasks were performed with respect to three different viewpoints (V1, V2, V3) and with four different execution styles (normal, with&nbsp; larger spatial scale, with different velocity profile, and with longer time duration). This resulted in a total of (3x4=12) twelve different contexts in which the tasks were performed. Each task was performed ten times in every context, resulting in a total of (10x3x4x10=1200) trials.</p> <p><strong>Experimental setup</strong></p> <p>The trials were recorded using a Krypton K600 camera from NIKON Metrology by tracking up to nine LED markers attached to the manipulated object. The 3D position of each LED marker was recorded with a sampling rate of 50 Hz and expected accuracy of 0.4mm with respect to the measurement frame of the camera system.</p> <p><strong>Data format</strong></p> <p>Every trial_xxx.mat file is a Matlab structure array. The trailing number xxx refers to the order in which the trials were performed. For every task:</p> <ul> <li>&nbsp;<em>trial_001.mat</em> up to <em>trial_040.mat&nbsp;</em>were recorded in sensor viewpoint 1. <ul> <li><em>trial_001.mat</em> up to <em>trial_010.mat </em>were executed with execution style:<em> normal.</em></li> <li><em>trial_011.mat</em> up to <em>trial_020.mat </em>were executed with execution style:<em> longer time duration.</em></li> <li><em>trial_021.mat</em> up to <em>trial_030.mat </em>were executed with execution style:<em> larger spatial scale.</em></li> <li><em>trial_031.mat</em> up to <em>trial_040.mat </em>were executed with execution style:<em> different velocity profile.</em></li> </ul> </li> <li>&nbsp;<em>trial_041.mat</em> up to <em>trial_080.mat </em>were recorded in sensor viewpoint 2.&nbsp; <ul> <li><em>trial_041.mat</em> up to <em>trial_050.mat </em>were executed with execution style:<em> normal.</em></li> <li><em>trial_051.mat</em> up to <em>trial_060.mat </em>were executed with execution style:<em> longer time duration.</em></li> <li><em>trial_061.mat</em> up to <em>trial_070.mat </em>were executed with execution style:<em> larger spatial scale.</em></li> <li><em>trial_071.mat</em> up to <em>trial_080.mat </em>were executed with execution style:<em> different velocity profile.</em></li> </ul> </li> <li><em>&nbsp;trial_081.mat</em> up to <em>trial_120.mat </em>were recorded in sensor viewpoint 3.&nbsp; <ul> <li><em>trial_081.mat</em> up to <em>trial_090.mat </em>were executed with execution style:<em> normal.</em></li> <li><em>trial_091.mat</em> up to <em>trial_100.mat </em>were executed with execution style:<em> longer time duration.</em></li> <li><em>trial_101.mat</em> up to <em>trial_110.mat </em>were executed with execution style:<em> larger spatial scale.</em></li> <li><em>trial_111.mat</em> up to <em>trial_120.mat </em>were executed with execution style:<em> different velocity profile.</em></li> </ul> </li> </ul> <p>The structure array trial_xxx.mat has the following fields:</p> <ul> <li>'number_of_timesamples': the total number of timesamples (N) for the recorded task,</li> <li>'K6C_12250_3_x': a 4xN matrix containing the 3D position coordinates of the LED marker expressed in millimeters. The trailing number x in 'K6C_12250_3_x' refers to the LED number, which can range from 1 to 9. <ul> <li>In case the LED marker was visible, the first, second and third row contain the x-, y-, and z-coordinates of the marker, respectively. The fourth row contains the zero value in this case.</li> <li>In case the LED marker was not visible, the first, second and third row contain zero values. &nbsp;The fourth row contains a non-zero value in this case.</li> </ul> </li> </ul>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
12
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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