Evaluating the morphological and metric sex of human crania using 3-dimensional (3D) technology

Berezowski, Victoria; Rogers, Tracy L.; Liscio, Eugene

doi:10.1007/s00414-020-02305-0

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…Other similar approaches to this problem that rely on 3D scanning technology and photogrammetry are novel enough to require additional testing to refine, and also rely on physical access to the crania in question and obtaining tens to hundreds of photos from all angles of a single skull (e.g. Berezowski, Rogers & Liscio 2020). Without ground-truthing, i.e.…”

Section: Resultsmentioning

confidence: 99%

Towards a Method for Discerning Sources of Supply within the Human Remains Trade via Patterns of Visual Dissimilarity and Computer Vision

Graham

Lane

Huffer

et al. 2020

Journal of Computer Applications in Archaeology

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While traders of human remains on Instagram will give some indication, their best estimate, or repeat hearsay, regarding the geographic origin or provenance of the remains, how can we assess the veracity of these claims when we cannot physically examine the remains? A novel image analysis using convolutional neural networks in a one-shot learning architecture with a triplet loss function is used to develop a range of 'distances' to known 'reference' images for a group of skulls with known provenances and a group of images of skulls from social media posts. Comparing the two groups enables us to predict a broad geographic 'ancestry' for any given skull depicted, using a mixture discriminant analysis, as well as a machine-learning model, on the image dissimilarity scores. It thus seems possible to assign, in broad strokes, that a particular skull has a particular geographic ancestry.

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Section: Resultsmentioning

confidence: 99%

Towards a Method for Discerning Sources of Supply within the Human Remains Trade via Patterns of Visual Dissimilarity and Computer Vision

Graham

Lane

Huffer

et al. 2020

Journal of Computer Applications in Archaeology

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“…Developing metric analyses specific to 3D models provides a valuable suite of new tools for forensic anthropologists, particularly as 3D imaging becomes a standard part of case documentation. Similarly, in cases where defence lawyers seek an independent forensic anthropological evaluation of the evidence, which often occurs well after the remains have been returned to the family, analyses can be completed from images or digital models [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

Missing and Murdered Indigenous Women and Girls in Canada: A New Population Affinity Assessment Technique to Aid in Identification Using 3D Technology

Cuerrier-Richer

2022

Forensic Sciences Research

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As of 2015, 204 cases of missing and murdered Indigenous women and girls (MMIWG) remained unsolved in Canada, making it a major concern for Canadian Indigenous communities, who are still pressing for the resolution of these cases. In forensic anthropology, the assessment of population affinity can be useful to help identify victims. Population affinity, previously referred to as ancestry, is evaluated based on morphological analyses, which examine the size and shape of skeletal features, and metric analyses, which utilise skeletal measurements. However, morphological analyses strongly depend on an anthropologist’s experience with human variation, which makes the analyses particularly challenging to reproduce and standardise. The purpose of this study is to improve the rigour of morphological analyses by using 3D technology to quantify relevant cranial nonmetric population affinity traits. As there is currently little morphological data available for the Canadian Indigenous population, this research aims to develop a new technique that could aid in the identification of MMIWG. The study comprised a total of 87 adult female crania, including 24 of Canadian Inuit origin, 50 of European descent and 13 of African descent. The samples were imaged using photogrammetry, then analysed using a 3D shape analysis in 3DS Max. Results show that this method is satisfactory in correctly evaluating population affinity with an accuracy of 87.36% (jackknifed: 80.46%) and an average repeatability of 97%. Unfortunately, the small Canadian Indigenous sample size impacted the applicability of the results and further research will be required before the technique can be used to aid in the identification of MMIWG in Canada.

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“…ReLU BN Conv N + = x out (5) Where Conv is a convolution operation, BN is a regularization operation, ReLU is a nonlinear operation, and © is a Channel level join operation.…”

Section: Dense Connectionsmentioning

confidence: 99%

“…With the development of science and technology, all kinds of social media platforms and mobile devices have been rapidly popularized and updated, and the utilization of biometric information such as face pictures, human video, and voice has begun to gain attention in daily life [1][2][3]. Commonly used biometrics include face recognition, fingerprint recognition, iris recognition, voiceprint recognition, etc., which are widely used in security, public transportation, and medical fields [4][5][6]. These intelligent applications can provide more reliable security and convenience for people's lives.…”

Section: Introductionmentioning

confidence: 99%

Research on Face Attribute Recognition Technology Based on Fine-Grained Features

Gao

2024

Applied Mathematics and Nonlinear Sciences

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This study explores fine-grained feature-based face attribute recognition techniques to enhance the accuracy of face recognition in low-resolution and complex environments. The article proposes a global feature extraction method and a local texture feature extraction method to extract global and regional features by enhancing feature reuse and information flow through dense connectivity and ShuffleNet V2 framework. Then, a multiscale feature exchange method is used to fuse different scale features to enhance the capture of detail information. Finally, efficient feature integration is achieved by the multiscale feature fusion method. Experimental results on the CK+ and FER2013 datasets show that the accuracy of this method on face expression recognition reaches 97.24% and 95.93%, respectively, and the average recognition accuracy in the face attribute recognition experiments on the CelebA dataset is 97.11%, which is significantly better than the comparison algorithm. In addition, the analysis of the recognition effect on low-resolution faces shows that this paper’s method achieves a recognition accuracy of 54.03% at a resolution of 15 × 15 and a high accuracy of over 99% at resolutions of 70 × 70 and above. These results show that the face attribute recognition technique based on fine-grained features proposed in this paper significantly improves recognition accuracy.

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Evaluating the morphological and metric sex of human crania using 3-dimensional (3D) technology

Cited by 4 publications

References 13 publications

Towards a Method for Discerning Sources of Supply within the Human Remains Trade via Patterns of Visual Dissimilarity and Computer Vision

Towards a Method for Discerning Sources of Supply within the Human Remains Trade via Patterns of Visual Dissimilarity and Computer Vision

Missing and Murdered Indigenous Women and Girls in Canada: A New Population Affinity Assessment Technique to Aid in Identification Using 3D Technology

Research on Face Attribute Recognition Technology Based on Fine-Grained Features

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