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Homologous multi-points warping: an algorithm for automatic 3D facial landmark


Citation

Opeoluwa, Agbolade Olalekan and Ahmad Nazri, Azree Shahrel and Yaakob, Razali and Abd Ghani, Abdul Azim and Cheah, Yoke Kqueen (2019) Homologous multi-points warping: an algorithm for automatic 3D facial landmark. In: 2019 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS 2019), 29 June 2019, Shah Alam, Selangor, Malaysia. (pp. 79-84).

Abstract

Over the decade scientists have been researching to know whether face recognition is performed holistically or with local feature analysis which has led to the proposition of various advanced methods in face recognition, especially using facial landmark. The current facial landmark methods in 3D are mathematically complex, contain insufficient landmarks, lack homology and full of localization error due to manual annotation. This paper proposes an Automatic Homologous Multi-Points Warping (AHMW) for 3D facial landmarking, experimented on three datasets using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks) by building a template mesh as a reference object and thereby applies the template to each of the targets on three datasets. The results show that the method is robust with minimum localization error (Stirling/ESRC:0.077; Bosphorus:0.088; and FRGC v2: 0.083).


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
Faculty of Medicine and Health Science
DOI Number: https://doi.org/10.1109/I2CACIS.2019.8825072
Publisher: IEEE
Keywords: 3D facial landmark; Landmark algorithm; Homologous facial points; 3D morphology; TPS warping; Localization error Introduction
Depositing User: Nabilah Mustapa
Date Deposited: 15 Jun 2020 06:54
Last Modified: 15 Jun 2020 06:54
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/I2CACIS.2019.8825072
URI: http://psasir.upm.edu.my/id/eprint/78146
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