Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study. C Turner, LM Pardo, DA Gunn, R Zillmer, S Mekić, F Liu, MA Ikram, CCW Klaver, PH Croll, A Goedegebure, K Trajanoska, F Rivadeneira, M Kavousi, GGO Brusselle, M Kayser, T Nijsten, J Bacardit.

3dMD Customer Research, Computer Science | Computer Vision, Genetics, Normative Study, 3dMDface, Computer Science

This is a cross-sectional study from an ongoing population based study from Rotterdam. Since 2010, the participants have been invited to participate in dermatological examinations that include taking 3D facial photographs with a static 3dMDtrio System (3dMD, Atlanta, USA).

Fully automated landmarking and facial segmentation on 3D photographs. B Berends, F Bielevelt, R Schreurs, et al.

3dMD Customer Research, Computer Science | Computer Vision, Genetics, Medical, Computer Science, Craniofacial/Cleft, Oral and Maxillofacial, Orthodontics, Orthognathic, Plastics

A deep learning-based approach for automated landmark extraction from 3dMD facial photographs was developed and its precision was evaluated. The results showed high precision and consistency in landmark annotation, comparable to manual and semi-automatic annotation methods.

Handy: Towards a high fidelity 3D hand shape and appearance model. R Potamias, S Ploumpis, S Moschoglou, V Triantafyllou and S Zafeiriou.

3dMD Customer Research, Computer Science | Computer Vision, 3dMDhand, Computer Science

We collected a large dataset comprising of textured 3D hand scans. Our hand data were captured during a special exhibition at the Science Museum, London. The capturing apparatus utilized for this task was a 3dMDhand5 system, which is an active stereo photogrammetry software-driven optics-based system, which produces high quality dense meshes.

Articulated Objects in Free-form Hand Interaction. Z Fan, O Taheri, D Tzionas, M Kocabas, M Kaufmann, MJ Black, O Hilliges.

3dMD Customer Research, Computer Science | Computer Vision, 3dMDhand, 3dMDbody, Computer Science, Computer Vision

Introducing ARCTIC – the first dataset of free-form interactions of hands and articulated objects. ARCTIC has 1.2M images paired with accurate 3D meshes for both hands and for objects that move and deform over time. The dataset also provides hand-object contact information.

3D Photography to Quantify the Severity of Metopic Craniosynostosis. MK Bruce, WH Tao, J Beiriger, C Christensen, MJ Pfaff, R Whitaker, JA Goldstein.

3dMD Customer Research, Medical, 3dMDhead, Computer Science, Craniofacial/Cleft, Plastics

Results of this study show that 3dMD photography is a valid alternative to CT for evaluation of head shape in MCS. Its use will provide an objective, quantifiable means of assessing outcomes in a rigorous manner while decreasing radiation exposure in this patient population.

Learning to Dress 3D People in Generative Clothing. Q Ma, J Yang, A Ranjan, S Pujades, G Pons-Moll, S Tang, MJ Black.

3dMD Customer Research, 3dMDbody, Computer Science, Temporal-3D Systems (4D), 4D 3dMDbody System, Computer Vision

Date: June 2020. Source: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA. Abstract: Three-dimensional human body models are widely used in the analysis of human pose and motion. Existing models, however, are learned from minimally-clothed 3D scans and thus do not generalize to the complexity of dressed people in common…

Learning Multi-human Optical Flow. A Ranjan, DT Hoffmann, D Tzionas et al.

3dMD Customer Research, Computer Science, Computer Vision

Date: January 2020. Source: International Journal of Computer Vision 128, 873–890 (2020). https://doi.org/10.1007/s11263-019-01279-w. Abstract: The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However, the training data used by them does not cover the…