2020 4D Body and 4D Hand Capture Exercise at the Science Museum, London
3dMDbody Capture at the Science Museum, London
The development of a 3D body scan and composition database to assess body size perception in psychological research. N Maalin, SM Mohamed, RS Kramer, et al.
Date: October 2019. Source: 3DBODY.TECH 2019 – 10th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland. Abstract: Recently, there has been a shift towards the use of 3D scanning technology in body size perception research. Based on limitations of previous methodologies there is a need to develop and validate female…
How the U.S. Sport Performance Apparel Industry Sizes Up to Female Plus Bodies. SL Solkolowski, J Silbert, L Griffin.
Date: October 2019. Source: 3DBODY.TECH 2019 – 10th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland. Abstract: In the United States, about 68% of the female population is greater than a size 14, or plus size [1]. This demographic represents a $21.4 billion industry [1]. Over the last five years,…
Development of a 3D Body Database to Improve Measures of Perceptual Male Body Image Distortion. SM Mohamed, N Maalin, RS Kramer, A Irvine, PL Cornelissen, KL Ritchie, MJ Tovee.
Date: October 2019. Source: 3DBODY.TECH 2019 – 10th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland. Abstract: There are important limitations in the current methodological stimuli being used in perceptual body image research among men, including a reliance on unrealistic images, a lack of biometric validity, and little consideration of…
Capture, Learning, and Synthesis of 3D Speaking Styles. D Cudeiro, T Bolkart, C Laidlaw, A Ranjan, MJ Black.
Date: June 2019. Source: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA. Proceedings Page(s): 10093-10103. Abstract: Audio-driven 3D facial animation has been widely explored, but achieving realistic, human-like performance is still unsolved. This is due to the lack of available 3D datasets, models, and standard evaluation metrics. To address…
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision. S Sanyal, T Bolkart, H Feng, MJ Black.
Date: June 2019. Source: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA. Proceedings Page(s): 7755-7764. Abstract: The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions. Robustness requires a large training set of in-the-wild…
Dense 3D Face Decoding Over 2500FPS: Joint Texture and Shape Convolutional Mesh Decoders. Y Zhou, Ji Deng, I Kotsia, S Zafeiriou.
Date: June 2019. Source: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA. Abstract: 3D Morphable Models (3DMMs) are statistical models that represent facial texture and shape variations using a set of linear bases and more particular Principal Component Analysis (PCA). 3DMMs were used as statistical priors for reconstructing 3D…
Smile dimensions in adult African American and Caucasian females and males. NM Souccar, DW Bowen, Z Syed, TA Swain, CH Kau, DM Sarver.
Date: May 2019. Source: Orthodontics & Craniofacial Research. https://doi.org/10.1111/ocr.12278. Objective: To test smile dimension variations in adult African American and Caucasian females and males. Setting and Sample Population: The University of Alabama at Birmingham School of Dentistry and Hospital. Three hundred and ninety‐four participants were recruited; African American females and males distributed over five age…
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation. S Moschoglou, S Ploumpis, MA Nicolaou et al.
Date: May 2019. Source: International Journal of Computer Vision (2020). https://doi.org/10.1007/s11263-020-01329-8. Abstract: Over the past few years, Generative Adversarial Networks (GANs) have garnered increased interest among researchers in Computer Vision, with applications including, but not limited to, image generation, translation, imputation, and super-resolution. Nevertheless, no GAN-based method has been proposed in the literature that can…
EDAR, LYPLAL1, PRDM16, PAX3, DKK1, TNFSF12, CACNA2D3, and SUPT3H gene variants influence facial morphology in a Eurasian population. Y Li, W Zhao, D Li et al.
Date: April 2019. Source: Human Genetics 138, 681–689 (2019). https://doi.org/10.1007/s00439-019-02023-7. Abstract: In human society, the facial surface is visible and recognizable based on the facial shape variation which represents a set of highly polygenic and correlated complex traits. Understanding the genetic basis underlying facial shape traits has important implications in population genetics, developmental biology, and…