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A Masked Facial Landmarks Localization Method Considering the Mask-Face Contact Characteristics

Published: 24 June 2022 Publication History

Abstract

At present, it has become normal for people to travel with masks. In order to meet the challenge of face recognition caused by mask occlusion, a new method for landmark localization of masked face was proposed in this study. Correspondingly, a 68-point shape model including face and mask was designed and the distribution of the related landmarks was pre-positioned according to the fitting characteristics between the face and mask. To generate a regressor with function of accurate localization of facial landmarks, the masked face dataset marked by the shape model was constructed; Meanwhile, the regression tree integration algorithm was used to accurately locate the pre-positioned landmarks of the masked face. By means of the method established in this study, the tested value of IPN and ION is respectively equal to 5.68 and 3.65, being less than those of other classical algorithms. The experimental results indicate that this method can achieve an acceptable landmark localization effect and is likely to provide certain technical supports for the masked face recognition.

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DSDE '22: Proceedings of the 2022 5th International Conference on Data Storage and Data Engineering
February 2022
124 pages
ISBN:9781450395724
DOI:10.1145/3528114
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 24 June 2022

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Author Tags

  1. Cascade regression tree
  2. Face recognition
  3. Mask Facial landmarks

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