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Dataset: Hand-pose estimation videos

<p>These digital artifacts provide a set of videos used as an input dataset for a qualitative evaluation of the pieces of software developed in the context of the Gesture Tracking for Low-End Virtual Reality Systems (GT4LEVRS) project. Each video shows a user making different sorts of gestures: static gestures, slow-moving gestures, and fast-moving gestures. The following files is provided</p> <ol> <li>&quot;2022-05-25 18-57-07.mp4&quot; shows a demonstration of the prototype</li> <li>&quot;Cenario estatico-20220624T180204Z-001.zip&quot; provides five set of videos of static gestures as follows: <ol> <li>Affirmative/OK signal (Folder: Afirmativo)</li> <li>Claw (Folder: Garra)</li> <li>Hang loose gesture (Folder: Hang loose)</li> <li>Opened Hand (Folder: Palma)</li> <li>Positive gesture (Folder: Positivo)</li> </ol> </li> <li>&quot;cenario lento-20220624T180237Z-001.zip&quot; provides five set of videos of low-moving gestures as follows: <ol> <li>Touching hands (Folder: maos encostando)</li> <li>Moving little finger (Folder: mindinho)</li> <li>Holding an object and moving it (Folder: objeto)</li> <li>Moving peace signal (Folder: paz)</li> <li>Moving fists (Folder: punho)</li> </ol> </li> <li>&quot;Cenario rapido-20220624T180245Z-001.zip&quot; provides five set of videos of fast-moving gestures as follows: <ol> <li>Goodbye (Folder: acenar)</li> <li>Moving indication (Folder: apontar)</li> <li>Throwing an object (Folder: arremessar objeto)</li> <li>Crossing hands (Folder: cruzar maos)</li> <li>Clapping hands (Folder: palmas)</li> </ol> </li> </ol> <p>Source code and other design artifacts can be found on Github: <a href="https://github.com/lesc-utfpr/gt4levrs">https://github.com/lesc-utfpr/gt4levrs</a></p> <p>This dataset was created in the context of a bachelor&#39;s final thesis in the Computer Engineering course of Federal University of Technology - Paran&aacute; (UTFPR), campus Curitiba, by Lucas Kuttner Amin and Rafael Hideo Toyomoto supervised by Prof. Marco Wehrmeister.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

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

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
4
Engagement
0

Topics

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