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• W3132173679 abstract "The Head Pose Estimation (HPE) is the study of the angular rotations of the head along the Pitch, Yaw, and Roll axes. Widely used in facial involving methods, as face frontalization, driver attention and best surveillance frame selection, is strongly related to facial features. In this study we examine the impact of facial expressions (FE) on HPE and, in particular, we put in relation the axis more affected by the error when a specific facial expression is observable. The HPE method chosen for this purpose is based on the Partitioned Iterated Function System (PIFS). For its construction this method is dependent on the facial appearance and self-similarity. Basing on this, and using a FER network, we observed that there is an evident relation between facial expressions and pose errors. This relation go thought the facial keypoints distances and can be discriminated along the three axes, by providing an estimate of the percentages of variation in errors related to a percentage of variation in distances." @default.
• W3132173679 created "2021-03-01" @default.
• W3132173679 creator A5018403922 @default.
• W3132173679 creator A5074877643 @default.
• W3132173679 date "2021-01-01" @default.
• W3132173679 modified "2023-09-25" @default.
• W3132173679 title "IFEPE: On the Impact of Facial Expression in Head Pose Estimation" @default.
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• W3132173679 doi "https://doi.org/10.1007/978-3-030-68821-9_41" @default.
• W3132173679 hasPublicationYear "2021" @default.
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