A 3D morphable model learnt from 10,000 faces

This is the final version of the article. It is the open access version, provided by the Computer Vision Foundation. Except for the watermark, it is identical to the IEEE published version. Available from IEEE via the DOI in this record.We present Large Scale Facial Model (LSFM) - a 3D Morphable Model (3DMM) automatically constructed from 9,663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM but also models tailored for specific age, gender or ethnicity groups. As an application example, we utilise the proposed model to perform age classification from 3D shape alone. Furthermore, we perform a systematic analysis of the constructed 3DMMs that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline. In addition, the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity are available on application to researchers involved in medically oriented research.J. Booth is funded by an EPSRC DTA from Imperial College London, and holds a Qualcomm Innovation Fellowship. A. Roussos is funded by the Great Ormond Street Hospital Childrens Charity (Face Value: W1037). The work of S. Zafeiriou was partially funded by the EPSRC project EP/J017787/1 (4D-FAB)

A 3D Morphable Model learnt from 10,000 faces

We present Large Scale Facial Model (LSFM) — a 3D Morphable Model (3DMM) automatically constructed from 9,663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM but also models tailored for specific age, gender or ethnicity groups. As an application example, we utilise the proposed model to perform age classification from 3D shape alone. Furthermore, we perform a systematic analysis of the constructed 3DMMs that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline. In addition, the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity are available on application to researchers involved in medically oriented research

Psychophysiological Measures of Cognitive Absorption

Cognitive absorption (CA) corresponds to a state of deep involvement with a software program. CA has widely been studied over the last decade in the IT literature using psychometric instruments. Measuring ongoing CA with psychometric tools requires interrupting a subject’s ongoing usage behavior to self-evaluate their level of absorption. Such interruptions may alter or contaminate the very CA state the researcher us attempting to measure. To circumvent this problem, we are investigating the effectiveness of psychophysiological measures of cognitive absorption. This paper reports preliminary results from an ongoing research project by looking at the correlation between electrodermal activity (EDA) and several dimensions of the CA construct

Nanotechnology for Stimulating Osteoprogenitor Differentiation.

BACKGROUND: Bone is the second most transplanted tissue and due to its complex structure, metabolic demands and various functions, current reconstructive options such as foreign body implants and autologous tissue transfer are limited in their ability to restore defects. Most tissue engineering approaches target osteoinduction of osteoprogenitor cells by modifying the extracellular environment, using scaffolds or targeting intracellular signaling mechanisms or commonly a combination of all of these. Whilst there is no consensus as to what is the optimal cell type or approach, nanotechnology has been proposed as a powerful tool to manipulate the biomolecular and physical environment to direct osteoprogenitor cells to induce bone formation. METHODS: Review of the published literature was undertaken to provide an overview of the use of nanotechnology to control osteoprogenitor differentiation and discuss the most recent developments, limitations and future directions. RESULTS: Nanotechnology can be used to stimulate osteoprogenitor differentiation in a variety of way. We have principally classified research into nanotechnology for bone tissue engineering as generating biomimetic scaffolds, a vector to deliver genes or growth factors to cells or to alter the biophysical environment. A number of studies have shown promising results with regards to directing ostroprogenitor cell differentiation although limitations include a lack of in vivo data and incomplete characterization of engineered bone. CONCLUSION: There is increasing evidence that nanotechnology can be used to direct the fate of osteoprogenitor and promote bone formation. Further analysis of the functional properties and long term survival in animal models is required to assess the maturity and clinical potential of this

The Science Behind the Springs: Using Biomechanics and Finite Element Modeling to Predict Outcomes in Spring-Assisted Sagittal Synostosis Surgery

Spring-assisted surgery for the correction of scaphocephaly has gained popularity over the past 2 decades. Our unit utilizes standardized torsional springs with a central helix for spring-assisted surgery. This design allows a high degree of accuracy and reproducibility of the force vectors and force distance curves. In this manuscript, we expand on the biomechanical testing and properties of these springs. Standardization of design has enabled us to study the springs on bench and in vivo and a comprehensive repository of calvarial remodeling and spring dynamics has been acquired and analyzed. Finite element modeling is a technique utilized to predict the outcomes of spring-assisted surgery. We have found this to be a useful tool, in planning our surgical strategy and improving outcomes. This technique has also contributed significantly to the process of informed consent preoperatively. In this article, we expand on our spring design and dynamics as well as the finite element modeling used to predict and improve outcomes. In our unit, this practice has led to a significant improvement in patient outcomes and parental satisfaction and we hope to make our techniques available to a wider audience

Reversible Luminescent Reaction of Amines with Copper(i) Cyanide

Copper(I) cyanide exposed to various liquid or vapor-phase amines (L) at ambient temperature produces a variety of visible photoluminescence colors via reversible formation of amine adducts. The adducts show phase matches to authentic (CuCN)Ln, n = 0.75–2.0, produced by heating CuCN with liquid amine

Combined soft and skeletal tissue modelling of normal and dysmorphic midface postnatal development

BACKGROUND: Midface hypoplasia as exemplified by Treacher Collins Syndrome (TCS) can impair appearance and function. Reconstruction involves multiple invasive surgeries with variable long-term outcomes. This study aims to describe normal and dysmorphic midface postnatal development through combined modelling of skeletal and soft tissues and to develop a surgical evaluation tool. MATERIALS AND METHODS: Midface skeletal and soft tissue surfaces were extracted from computed tomography scans of 52 control and 14 TCS children, then analysed using dense surface modelling. The model was used to describe midface growth, morphology, and asymmetry, then evaluate postoperative outcomes. RESULTS: Parameters responsible for the greatest variation in midface size and shape showed differences between TCS and controls with close alignment between skeletal and soft tissue models. TCS children exhibited midface dysmorphology and hypoplasia when compared with controls. Asymmetry was also significantly higher in TCS midfaces. Combined modelling was used to evaluate the impact of surgery in one TCS individual who showed normalisation immediately after surgery but reversion towards TCS dysmorphology after 1 year. CONCLUSION: This is the first quantitative analysis of postnatal midface development using combined modelling of skeletal and soft tissues. We also provide an approach for evaluation of surgical outcomes, laying the foundations for future development of a preoperative planning tool

Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly

Sagittal Craniosynostosis (SC) is a congenital craniofacial malformation, involving premature sagittal suture ossification; spring-assisted cranioplasty (SAC)–insertion of metallic distractors for skull reshaping–is an established method for treating SC. Surgical outcomes are predictable using numerical modelling, however published methods rely on computed tomography (CT) scans availability, which are not routinely performed. We investigated a simplified method, based on radiation-free 3D stereophotogrammetry scans. Eight SAC patients (age 5.1 ± 0.4 months) with preoperative CT and 3D stereophotogrammetry scans were included. Information on osteotomies, spring model and post-operative spring opening were recorded. For each patient, two preoperative models (PREOP) were created: i) CT model and ii) S model, created by processing patient specific 3D surface scans using population averaged skin and skull thickness and suture locations. Each model was imported into ANSYS Mechanical (Analysis System Inc., Canonsburg, PA) to simulate spring expansion. Spring expansion and cranial index (CI - skull width over length) at times equivalent to immediate postop (POSTOP) and follow up (FU) were extracted and compared with in-vivo measurements. Overall expansion patterns were very similar for the 2 models at both POSTOP and FU. Both models had comparable outcomes when predicting spring expansion. Spring induced CI increase was similar, with a difference of 1.2%±0.8% for POSTOP and 1.6%±0.6% for FU. This work shows that a simplified model created from the head surface shape yields acceptable results in terms of spring expansion prediction. Further modelling refinements will allow the use of this predictive tool during preoperative planning