Craniofacial Reconstruction Method Based on Region Fusion Strategy
المؤلفون المشاركون
Wen, Yang
Mingquan, Zhou
Pengyue, Lin
Guohua, Geng
Xiaoning, Liu
Kang, Li
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-04
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Craniofacial reconstruction is to estimate a person’s face model from the skull.
It can be applied in many fields such as forensic medicine, archaeology, and face animation.
Craniofacial reconstruction is based on the relationship between the skull and the face to reconstruct the facial appearance from the skull.
However, the craniofacial structure is very complex and the relationship is not the same in different craniofacial regions.
To better represent the shape changes of the skull and face and make better use of the correlation between different local regions, a new craniofacial reconstruction method based on region fusion strategy is proposed in this paper.
This method has the flexibility of finding the nonlinear relationship between skull and face variables and is easy to solve.
Firstly, the skull and face are divided into five corresponding local regions; secondly, the five regions of skull and face are mapped to low-dimensional latent space using Gaussian process latent variable model (GP-LVM), and the nonlinear features between skull and face are extracted; then, least square support vector regression (LSSVR) model is trained in latent space to establish the mapping relationship between skull region and face region; finally, perform regional fusion to achieve overall reconstruction.
For the unknown skull, first divide the region, then project it into the latent space of the skull region, then use the trained LSSVR model to reconstruct the face of the corresponding region, and finally perform regional fusion to realize the face reconstruction of the unknown skull.
The experimental results show that the method is effective.
Compared with other regression methods, our method is optimal.
In addition, we add attributes such as age and body mass index (BMI) to the mappings to achieve face reconstruction with different attributes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wen, Yang& Mingquan, Zhou& Pengyue, Lin& Guohua, Geng& Xiaoning, Liu& Kang, Li. 2020. Craniofacial Reconstruction Method Based on Region Fusion Strategy. BioMed Research International،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1137721
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wen, Yang…[et al.]. Craniofacial Reconstruction Method Based on Region Fusion Strategy. BioMed Research International No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1137721
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wen, Yang& Mingquan, Zhou& Pengyue, Lin& Guohua, Geng& Xiaoning, Liu& Kang, Li. Craniofacial Reconstruction Method Based on Region Fusion Strategy. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1137721
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1137721
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر