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Head Pose

Ba, Silèye; Odobez, Jean-Marc

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  <identifier identifierType="URL"></identifier>
      <creatorName>Ba, Silèye</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0003-4581-9880</nameIdentifier>
      <affiliation>Idiap Research Institute</affiliation>
      <creatorName>Odobez, Jean-Marc</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-9537-9898</nameIdentifier>
      <affiliation>Idiap Research Institute</affiliation>
    <title>Head Pose</title>
    <subject>head pose</subject>
    <subject>meeting room</subject>
    <subject>low resolution</subject>
    <date dateType="Issued">2005-01-01</date>
  <resourceType resourceTypeGeneral="Dataset"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.34777/2nqa-1907</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf"></relatedIdentifier>
    <rights rightsURI="info:eu-repo/semantics/restrictedAccess">Restricted Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;The objective of Head Pose dataset was to construct a video database allowing to perform quantitative evaluation of algorithms extracting information related to the head pose of people, such as head tracking and pose estimation algorithms, or focus of attention analysis.&lt;/p&gt;

&lt;p&gt;The database comprises two sets of video involving people engaged in natural activities. In the first one, people are participating in meetings and are debating statements displayed on a screen. In the second set, persons are performing some tasks in their office. In all cases, the head pose of people is continuously annotated thanks to the use of a 3D location and orientation magnetic trackers called flock of birds. In both sets, the head pose of 16 different persons has been recorded.&lt;/p&gt;

&lt;p&gt;This database building was done in the context of two projects.&lt;/p&gt;

	&lt;li&gt;Multi-Object, Multi-Camera Tracking and Activity Recognition (MUCATAR) project which is aimed at developping probabilistic algorithms for joint people tracking and activity recognition. The MUCATAR project is funded by the swiss National Center of Competence in Research (NCCR) on Interactive Multimodal Information Management (IM)2 which is devoted to the advancement of research, and the development of prototypes, in the field of man-machine interaction.&lt;/li&gt;
	&lt;li&gt;AMI (Augmented Multi-party Interaction), an EC IST funded projects which targets the advancement of computer enhanced multi-modal interaction in the context of meetings.&lt;/li&gt;



&lt;p&gt;Sileye Ba and Jean-Marc Odobez&amp;nbsp;: &amp;ldquo;Evaluation of Multiple Cues Head Pose Estimation Algorithms in Natural Environments&amp;rdquo; in Proceedings of the International Conference on Multimedia &amp;amp; Expo (ICME), Amsterdam, 2005.&lt;/p&gt;</description>
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