Statistical Modeling of Craniofacial Shape and Texture

We present a fully-automatic statistical 3D shape modeling approach and apply it to a large dataset of 3D images, the Headspace dataset, thus generating the first public shape-and-texture 3D Morphable Model (3DMM) of the full human head. Our approach is the first to employ a template that adapts to the dataset subject before dense morphing. This is fully automatic and achieved using 2D facial landmarking, projection to 3D shape, and mesh editing. In dense template morphing, we improve on the well-known Coherent Point Drift algorithm, by incorporating iterative data-sampling and alignment. Our evaluations demonstrate that our method has better performance in correspondence accuracy and modeling ability when compared with other competing algorithms. We propose a texture map refinement scheme to build high quality texture maps and texture model. We present several applications that include the first clinical use of craniofacial 3DMMs in the assessment of different types of surgical intervention applied to a craniosynostosis patient group

Statistical Modelling of Craniofacial Shape

With prior knowledge and experience, people can easily observe rich shape and texture variation for a certain type of objects, such as human faces, cats or chairs, in both 2D and 3D images. This ability helps us recognise the same person, distinguish different kinds of creatures and sketch unseen samples of the same object class. The process of capturing this prior knowledge is mathematically interpreted as statistical modelling. The outcome is a morphable model, a vector space representation of objects, that captures the variation of shape and texture. This thesis presents research aimed at constructing 3DMMs of craniofacial shape and texture using new algorithms and processing pipelines to offer enhanced modelling abilities over existing techniques. In particular, we present several fully automatic modelling approaches and apply them to a large dataset of 3D images of the human head, the Headspace dataset, thus generating the first public shape-and- texture 3D Morphable Model (3DMM) of the full human head. We call this the Liverpool-York Head Model, reflecting the data collection and statistical modelling respectively. We also explore the craniofacial symmetry and asymmetry in template morphing and statistical modelling. We propose a Symmetry-aware Coherent Point Drift (SA-CPD) algorithm, which mitigates the tangential sliding problem seen in competing morphing algorithms. Based on the symmetry-constrained correspondence output of SA-CPD, we present a symmetry-factored statistical modelling method for craniofacial shape. Also, we propose an iterative process of refinement for a 3DMM of the human ear that employs data augmentation. Then we merge the proposed 3DMMs of the ear with the full head model. As craniofacial clinicians like to look at head profiles, we propose a new pipeline to build a 2D morphable model of the craniofacial sagittal profile and augment it with profile models from frontal and top-down views. Our models and data are made publicly available online for research purposes

A Radiation-Free Classification Pipeline for Craniosynostosis Using Statistical Shape Modeling

Background: Craniosynostosis is a condition caused by the premature fusion of skull sutures, leading to irregular growth patterns of the head. Three-dimensional photogrammetry is a radiation-free alternative to the diagnosis using computed tomography. While statistical shape models have been proposed to quantify head shape, no shape-model-based classification approach has been presented yet. Methods: We present a classification pipeline that enables an automated diagnosis of three types of craniosynostosis. The pipeline is based on a statistical shape model built from photogrammetric surface scans. We made the model and pathology-specific submodels publicly available, making it the first publicly available craniosynostosis-related head model, as well as the first focusing on infants younger than 1.5 years. To the best of our knowledge, we performed the largest classification study for craniosynostosis to date. Results: Our classification approach yields an accuracy of 97.8 %, comparable to other state-of-the-art methods using both computed tomography scans and stereophotogrammetry. Regarding the statistical shape model, we demonstrate that our model performs similar to other statistical shape models of the human head. Conclusion: We present a state-of-the-art shape-model-based classification approach for a radiation-free diagnosis of craniosynostosis. Our publicly available shape model enables the assessment of craniosynostosis on realistic and synthetic data

A Data-augmented 3D Morphable Model of the Ear

Morphable models are useful shape priors for biometric recognition tasks. Here we present an iterative process of refinement for a 3D Morphable Model (3DMM) of the human ear that employs data augmentation. The process employs the following stages 1) landmark-based 3DMM fitting; 2) 3D template deformation to overcome noisy over-fitting; 3) 3D mesh editing, to improve the fit to manual 2D landmarks. These processes are wrapped in an iterative procedure that is able to bootstrap a weak, approximate model into a significantly better model. Evaluations using several performance metrics verify the improvement of our model using the proposed algorithm. We use this new 3DMM model-booting algorithm to generate a refined 3D morphable model of the human ear, and we make this new model and our augmented training dataset public

The analysis of facial beauty: an emerging area of research in pattern analysis

Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application

DISTRIBUTED ELECTRO-MECHANICAL ACTUATION AND SENSING SYSTEM DESIGN FOR MORPHING STRUCTURES

Smart structures, able to sense changes of their own state or variations of the environment they’re in, and capable of intervening in order to improve their performance, find themselves in an ever-increasing use among numerous technology fields, opening new frontiers within advanced structural engineering and materials science. Smart structures represent of course a current challenge for the application on the aircrafts. A morphing structure can be considered as the result of the synergic integration of three main systems: the structural system, based on reliable kinematic mechanisms or on compliant elements enabling the shape modification, the actuation and control systems, characterized by embedded actuators and robust control strategies, and the sensing system, usually involving a network of sensors distributed along the structure to monitor its state parameters. Technologies with ever increasing maturity level are adopted to assure the consolidation of products in line with the aeronautical industry standards and fully compliant with the applicable airworthiness requirements. Until few years ago, morphing wing technology appeared an utopic solution. In the aeronautical field, airworthiness authorities demand a huge process of qualification, standardization, and verification. Essential components of an intelligent structure are sensors and actuators. The actual technological challenge, envisaged in the industrial scenario of “more electric aircraft”, will be to replace the heavy conventional hydraulic actuators with a distributed strategy comprising smaller electro-mechanical actuators. This will bring several benefit at the aircraft level: firstly, fuel savings. Additionally, a full electrical system reduces classical drawbacks of hydraulic systems and overall complexity, yielding also weight and maintenance benefits. At the same time, a morphing structure needs a real-time strain monitoring system: a nano-engineered polymer capable of densely distributed strain sensing can be a suitable solution for this kind of flying systems. Piezoresistive carbon nanotubes can be integrated as thin films coated and integrated with composite to form deformable self-sensing materials. The materials actually become sensors themselves without using external devices, embedded or attached. This doctoral thesis proposes a multi-disciplinary investigation of the most modern actuation and sensing technologies for variable-shaped devices mainly intended for large commercial aircraft. The personal involvement in several research projects with numerous international partners - during the last three years - allowed for exploiting engineering outcomes in view of potential certification and industrialization of the studied solutions. Moving from a conceptual survey of the smart systems that introduces the idea of adaptive aerodynamic surfaces and main research challenges, the thesis presents (Chapter 1) the current worldwide status of morphing technologies as well as industrial development expectations. The Ph.D. programme falls within the design of some of the most promising and potentially flyable solutions for performance improvement of green regional aircrafts. A camber-morphing aileron and a multi-modal flap are herein analysed and assessed as subcomponents involved for the realization of a morphing wing. An innovative camber-morphing aileron was proposed in CRIAQ MD0-505, a joint Canadian and Italian research project. Relying upon the experimental evidence within the present research, the issue appeared concerns the critical importance of considering the dynamic modelling of the actuators in the design phase of a smart device. The higher number of actuators involved makes de facto the morphing structure much more complex. In this context (Chapter 2), the action of the actuators has been modelled within the numerical model of the aileron: the comparison between the modal characteristics of numerical predictions and testing activities has shown a high level of correlation. Morphing structures are characterized by many more degrees of freedom and increased modal density, introducing new paradigms about modelling strategies and aeroelastic approaches. These aspects affect and modify many aspects of the traditional aeronautical engineering process, like simulation activity, design criteria assessment, and interpretation of the dynamic response (Chapter 3). With respect the aforementioned aileron, sensitivity studies were carried out in compliance with EASA airworthiness requirements to evaluate the aero-servo-elastic stability of global system with respect to single and combined failures of the actuators enabling morphing. Moreover, the jamming event, which is one of the main drawbacks associated with the use of electro-mechanical actuators, has been duly analyzed to observe any dynamic criticalities. Fault & Hazard Analysis (FHA) have been therefore performed as the basis for application of these devices to real aircraft. Nevertheless, the implementation of an electro-mechanical system implies several challenges related to the integration at aircraft system level: the practical need for real-time monitoring of morphing devices, power absorption levels and dynamic performance under aircraft operating conditions, suggest the use of a ground-based engineering tool, i.e. “iron bird”, for the physical integration of systems. Looking in this perspective, the Chapter 4 deals with the description of an innovative multi-modal flap idealized in the Clean Sky - Joint Technology Initiative research scenario. A distributed gear-drive electro-mechanical actuation has been fully studied and validated by an experimental campaign. Relying upon the experience gained, the encouraging outcomes led to the second stage of the project, Clean Sky 2 - Airgreen 2, encompassing the development of a more robotized flap for next regional aircraft. Numerical and experimental activities have been carried out to support the health management process in order to check the EMAs compatibility with other electrical systems too. A smart structure as a morphing wing needs an embedded sensing system in order to measure the actual deformation state as well as to “monitor” the structural conditions. A new possible approach in order to have a distributed light-weight system consists in the development of polymer-based materials filled with conductive smart fillers such as carbon nanotubes (CNTs). The thesis ends with a feasibility study about the incorporation of carbon nanomaterials into flexible coatings for composite structures (Chapter 5). Coupons made of MWCNTs embedded in typical aeronautic epoxy formulation were prepared and tested under different conditions in order to better characterize their sensing performance. Strain sensing properties were compared to commercially available strain gages and fiber optics. The results were obtained in the last training year following the involvement of the author in research activities at the University of Salerno and Materials and Structures Centre - University of Bath. One of the issues for the next developments is to consolidate these novel technologies in the current and future European projects where the smart structures topic is considered as one of the priorities for the new generation aircrafts. It is remarkable that scientists and aeronautical engineers community does not stop trying to create an intelligent machine that is increasingly inspired by nature. The spirit of research, the desire to overcome limits and a little bit of imagination are surely the elements that can guide in achieving such an ambitious goal