<?xml version="1.0" encoding="UTF-8"?>
<resource xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4/metadata.xsd"
          xmlns="http://datacite.org/schema/kernel-4"
          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <identifier identifierType="DOI">10.34622/datarepositorium/1S8QVP</identifier>
    <creators><creator><creatorName>R. P. Rodrigues, Nelson</creatorName><nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0000-0002-7697-1749</nameIdentifier><affiliation>(University of Minho)</affiliation></creator><creator><creatorName>M. C. da Costa, Nuno</creatorName></creator><creator><creatorName>Novais, Rita</creatorName><affiliation>(University of Minho)</affiliation></creator><creator><creatorName>Fonseca, Jaime</creatorName><affiliation>(University of Minho)</affiliation></creator><creator><creatorName>Cardoso, Paulo</creatorName><affiliation>(University of Minho)</affiliation></creator><creator><creatorName>Borges, Joao</creatorName></creator></creators>
    <titles>
        <title>MoLa InCar AR: Dataset for Action Recognition</title>
    </titles>
    <publisher>Repositório de Dados da Universidade do Minho</publisher>
    <publicationYear>2022</publicationYear>
    <resourceType resourceTypeGeneral="Dataset"/>
    <relatedIdentifiers><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/GQ0EZK</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/QAVM2B</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/DKKVFQ</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/CLJG3N</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/QN1INY</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/DGMCRY</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/TTFSSO</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/8AUIUJ</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/KUXEXY</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/B9TBX7</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/VN58R0</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/KDK0Q0</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/QIZKRY</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/PP16CE</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/BXXHPP</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/LPKOCV</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/R1SIGT</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/HTBEWG</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/BCXIEO</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/FANUBE</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/2DLOPY</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/48R3VW</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/WNUWD1</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/MAT3YR</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/NDLFVF</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/UDKGZR</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/3STEUD</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/DM7OJR</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/EEQCFX</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/S72W4Q</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/C8ZZYZ</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/M7UAYF</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/DVJDHO</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/FDMDNI</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/HQMFWJ</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/ALPWNN</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/ZX3P7M</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/QX3SX0</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/GND7O8</relatedIdentifier><relatedIdentifier relatedIdentifierType="DOI" relationType="HasPart">doi:10.34622/datarepositorium/1S8QVP/VEQ7BW</relatedIdentifier></relatedIdentifiers>
    <descriptions>
        <description descriptionType="Abstract">We introduce a dataset to train human action recognition inside the vehicle focusing on violence detection. The dataset was recorded with RGB, Depth, Thermal and Event-based data. Results: The resulting dataset contains 6 400 video samples and more than 3 million frames, collected from sixteen distinct subjects. The dataset contains 58 action classes, including violent and neutral (i.e., non-violent) activities.</description>
    </descriptions>
    <contributors><contributor contributorType="ContactPerson"><contributorName>R. P. Rodrigues, Nelson</contributorName><affiliation>(University of Minho)</affiliation></contributor><contributor contributorType="Producer"><contributorName>R. P. Rodrigues, Nelson</contributorName><affiliation>(University of Minho)</affiliation></contributor></contributors>
</resource>
