Journal article Open Access

A Low-Power VGA Vision Sensor with Embedded Event Detection for Outdoor Edge Applications

Zou, Yu; Gottardi, Massimo; Lecca, Michela; Perenzoni, Matteo


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  <identifier identifierType="URL">https://zenodo.org/record/4059748</identifier>
  <creators>
    <creator>
      <creatorName>Zou, Yu</creatorName>
      <givenName>Yu</givenName>
      <familyName>Zou</familyName>
      <affiliation>FBK</affiliation>
    </creator>
    <creator>
      <creatorName>Gottardi, Massimo</creatorName>
      <givenName>Massimo</givenName>
      <familyName>Gottardi</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0742-4642</nameIdentifier>
      <affiliation>FBK</affiliation>
    </creator>
    <creator>
      <creatorName>Lecca, Michela</creatorName>
      <givenName>Michela</givenName>
      <familyName>Lecca</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7961-0212</nameIdentifier>
      <affiliation>FBK</affiliation>
    </creator>
    <creator>
      <creatorName>Perenzoni, Matteo</creatorName>
      <givenName>Matteo</givenName>
      <familyName>Perenzoni</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8777-1593</nameIdentifier>
      <affiliation>FBK</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Low-Power VGA Vision Sensor with Embedded Event Detection for Outdoor Edge Applications</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Background subtraction, event detection, local binary pattern, low-power vision sensors, motion detection</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-07-13</date>
  </dates>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4059748</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/JSSC.2020.3005759</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;We report on a low-power VGA vision sensor embedding event-detection capabilities targeted to battery-powered vision processing at the edge. The sensor relies on an always-on double-threshold dynamic background subtraction (DT-DBS) algorithm. The resulting motion bitmap is de-noised, projected along xy-axes of the array of pixels and filtered to robustly detect moving targets even in noisy outdoor scenarios. The chip operates in motion detection (MD), applied on a QQVGA sub-sampled image, looking for anomalous motion in the scene at 344 &amp;mu;W, and in imaging mode (IM), delivering full-resolution gray-scale images with associated local binary pattern (LBP) coding and motion bitmaps at 8 frames/s and 1.35 mW. The 4-&amp;mu;m pixel vision sensor is manufactured in a 110-nm 1P4M CMOS and occupies 25.4 mm&amp;sup2;.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/653355/">653355</awardNumber>
      <awardTitle>FOREnsic evidence gathering autonomous seNSOR</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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