Détection de visages en domaines compressés

Ce mémoire aborde le problème de la détection de visages à partir d'une image compressée. Il touche également à un problème connexe qui est la qualité des standards de compression et l'estimation de celle-ci. Ce mémoire est organisé sous la forme d'une introduction générale sur la détection de visages et de deux articles soumis à des conférences internationales. Le premier article propose une amélioration de la méthode classique pour comparer la qualité de deux standards. Le deuxième propose une méthode de décompression spécialisée pour faire fonctionner le détecteur de visages de Viola-Jones dans le domaine compressé

Productive Waterscapes in the West-South of Europe: Using Circular Economy Theory to Drive the Change from a Linear to a Circular Paradigm of Water and Greenways

Re-thinking, re-design, re-use are the keywords of the ecological economy that seek to link social, economic and environmental aspects together. These fundamental principles can be observed in the theories proposed by the Ellen MacArthur Foundation and are the basis of the new discipline called “Circular Economy.” Recent studies seem to advise that the transition to sustainability (Foro Springtif 2015) is being stopped for political, cultural, economic, and infrastructural reasons. This article shows and discusses, through presenting different case studies, the situation of the circular economy applied to peri-urban greenways and waterfronts. Presenting obstacles and opportunities, the researchers want to give some advice and trace a method capable of shifting from a linear economy to a circular economy in urbanism and land management. The focus on the historical link between cities and water, shows that the linear economy is in a continuous relationship of love and hate, thanks to the force of the water and the engineering knowledge of the human beings: a strong relationship when water was used for the industrial revolution, of distance and fear when the water was wide and polluted. In the last decade, this relationship seems to be skipped. Thanks to climate change, flood events appear to occur with increasing frequency and intensity, but municipalities allow industry and logistical compounds to settle near the rivers, affecting the aquifer. The paradigm shift to a circular economy should include a democratic society where citizens are promoting different lifestyles and push the decision-makers to develop new strategy and policy. This new vision is well applied in different contexts but doesn’t seem to be able to face and influence the protection of the last ecological corridors present in peri-urban areas, the reclaiming of derelict and polluted industrial areas, and the development of a virtuous approach to new industrial and logistical settlements. The conclusion of the paper collects positive case studies, using them to show some methods and strategies able to drive the change through a new balance between ecological restoration and economic development. Re-thinking, re-design, re-use are keywords of the ecological economy that seek to link social, economic and environmental aspect together

Learning objects model and context for recognition and localisation

Cette thèse traite des problèmes de modélisation, reconnaissance, localisation et utilisation du contexte pour la manipulation d'objets par un robot. Le processus de modélisation se divise en quatre composantes : le système réel, les données capteurs, les propriétés à reproduire et le modèle. En spécifiant chacune des ces composantes, il est possible de définir un processus de modélisation adapté au problème présent, la manipulation d'objets par un robot. Cette analyse mène à l'adoption des descripteurs de texture locaux pour la modélisation. La modélisation basée sur des descripteurs de texture locaux a été abordé dans de nombreux travaux traitant de structure par le mouvement (SfM) ou de cartographie et localisation simultanée (SLAM). Les méthodes existantes incluent Bundler, Roboearth et 123DCatch. Pourtant, aucune de ces méthodes n'a recueilli le consensus. En effet, l'implémentation d'une approche similaire montre que ces outils sont difficiles d'utilisation même pour des utilisateurs experts et qu'ils produisent des modèles d'une haute complexité. Cette complexité est utile pour fournir un modèle robuste aux variations de point de vue. Il existe deux façons pour un modèle d'être robuste : avec le paradigme des vues multiple ou celui des descripteurs forts. Dans le paradigme des vues multiples, le modèle est construit à partir d'un grand nombre de points de vue de l'objet. Le paradigme des descripteurs forts compte sur des descripteurs résistants aux changements de points de vue. Les expériences réalisées montrent que des descripteurs forts permettent d'utiliser un faible nombre de vues, ce qui résulte en un modèle simple. Ces modèles simples n'incluent pas tout les point de vus existants mais les angles morts peuvent être compensés par le fait que le robot est mobile et peut adopter plusieurs points de vue. En se basant sur des modèles simples, il est possible de définir des méthodes de modélisation basées sur des images seules, qui peuvent être récupérées depuis Internet. A titre d'illustration, à partir d'un nom de produit, il est possible de récupérer des manières totalement automatiques des images depuis des magasins en ligne et de modéliser puis localiser les objets désirés. Même avec une modélisation plus simple, dans des cas réel ou de nombreux objets doivent être pris en compte, il se pose des problèmes de stockage et traitement d'une telle masse de données. Cela se décompose en un problème de complexité, il faut traiter de nombreux modèles rapidement, et un problème d'ambiguïté, des modèles peuvent se ressembler. L'impact de ces deux problèmes peut être réduit en utilisant l'information contextuelle. Le contexte est toute information non issue des l'objet lui même et qui aide a la reconnaissance. Ici deux types de contexte sont abordés : le lieu et les objets environnants. Certains objets se trouvent dans certains endroits particuliers. En connaissant ces liens lieu/objet, il est possible de réduire la liste des objets candidats pouvant apparaître dans un lieu donné. Par ailleurs l'apprentissage du lien lieu/objet peut être fait automatiquement par un robot en modélisant puis explorant un environnement. L'information appris peut alors être fusionnée avec l'information visuelle courante pour améliorer la reconnaissance. Dans les cas des objets environnants, un objet peut souvent apparaître au cotés d'autres objets, par exemple une souris et un clavier. En connaissant la fréquence d'apparition d'un objet avec d'autres objets, il est possible de réduire la liste des candidats lors de la reconnaissance. L'utilisation d'un Réseau de Markov Logique est particulièrement adaptée à la fusion de ce type de données. Cette thèse montre la synergie de la robotique et du contexte pour la modélisation, reconnaissance et localisation d'objets.This Thesis addresses the modeling, recognition, localization and use of context for objects manipulation by a robot. We start by presenting the modeling process and its components: the real system, the sensors' data, the properties to reproduce and the model. We show how, by specifying each of them, one can define a modeling process adapted to the problem at hand, namely object manipulation by a robot. This analysis leads us to the adoption of local textured descriptors for object modeling. Modeling with local textured descriptors is not a new concept, it is the subject of many Structure from Motion (SfM) or Simultaneous Localization and Mapping (SLAM) works. Existing methods include bundler, roboearth modeler and 123DCatch. Still, no method has gained widespread adoption. By implementing a similar approach, we show that they are hard to use even for expert users and produce highly complex models. Such complex techniques are necessary to guaranty the robustness of the model to view point change. There are two ways to handle the problem: the multiple views paradigm and the robust features paradigm. The multiple views paradigm advocate in favor of using a large number of views of the object. The robust feature paradigm relies on robust features able to resist large view point changes. We present a set of experiments to provide an insight into the right balance between both. By varying the number of views and using different features we show that small and fast models can provide robustness to view point changes up to bounded blind spots which can be handled by robotic means. We propose four different methods to build simple models from images only, with as little a priori information as possible. The first one applies to planar or piecewise planar objects and relies on homographies for localization. The second approach is applicable to objects with simple geometry, such as cylinders or spheres, but requires many measures on the object. The third method requires the use of a calibrated 3D sensor but no additional information. The fourth technique doesn't need a priori information at all. We apply this last method to autonomous grocery objects modeling. From images automatically retrieved from a grocery store website, we build a model which allows recognition and localization for tracking. Even using light models, real situations ask for numerous object models to be stored and processed. This poses the problems of complexity, processing multiple models quickly, and ambiguity, distinguishing similar objects. We propose to solve both problems by using contextual information. Contextual information is any information helping the recognition which is not directly provided by sensors. We focus on two contextual cues: the place and the surrounding objects. Some objects are mainly found in some particular places. By knowing the current place, one can restrict the number of possible identities for a given object. We propose a method to autonomously explore a previously labeled environment and establish a correspondence between objects and places. Then this information can be used in a cascade combining simple visual descriptors and context. This experiment shows that, for some objects, recognition can be achieved with as few as two simple features and the location as context. The objects surrounding a given object can also be used as context. Objects like a keyboard, a mouse and a monitor are often close together. We use qualitative spatial descriptors to describe the position of objects with respect to their neighbors. Using a Markov Logic Network, we learn patterns in objects disposition. This information can then be used to recognize an object when surrounding objects are already identified. This Thesis stresses the good match between robotics, context and objects recognition

Assessing the Robustness of a UAS Detect & Avoid Algorithm

International audienceIn this article, we evaluate the robustness of a detect and avoid algorithm designed for the integration of UASs in terminal control areas. This assessment relies on a realistic modeling of navigation accuracy on positions and velocities and was carried out on thousands of scenarios built from recorded commercial traffic trajectories. The tested scenarios involved two different types of UASs – flying at 80 kts and 160 kts – with various missions, and three strategies for separation: one focussing on the separation distance, one focussing on the UAS mission and and combination of both. Fast-time simulation was used to evaluate each scenario against a wide range of accuracy levels corresponding to required navigation precision standards and linked to on-board navigation and communication systems. Experiments reveal a strong robustness of the separation algorithm up to relatively high uncertainty levels, indicating that UASs equipped with low accuracy navigation systems can still manage proper separation. However, the maneuvering cost for separation increases when the accuracy deteriorates. Nevertheless, a UAS with GPS-based navigation in a collaborative environment (e.g. aircraft providing their navigation parameters through ADS-B) can expect robustness at a reasonable cost

Full-Arch, Implant-Fixed Complete Dentures in Monolithic Zirconia and Titanium: A Digital Workflow to Maximize Cost Effectiveness

Different techniques can be used to design and manufacture a full-arch, implant-supported prosthesis, and different materials can be chosen for its production, each with its advantages and limitations. One of the possibilities provided by digital tools is their ability to maintain low costs to give more patients the chance to choose this commonly expensive treatment. The present work aims to present a protocol for the realization of full-arch, implant-fixed complete dentures (IFCDs) in monolithic zirconia and titanium. When the analogic master model is obtained, it is scanned to perform the digital wax-up, and the two parts of the prosthesis—a bar in titanium and an aesthetic component in monolithic zirconia—are milled. The dental team must then verify the precision of the milled components on the master model, so that they can be cemented together and delivered to the patient. This technique offers different advantages, in terms of cost sustainability, minimal wear risk for the prosthesis and its antagonists, and ease of re-intervening in the case of complications. The main limitations of the technique may lie in the aesthetic needs of the patient, because of the relatively poor aesthetic performance of monolithic zirconia and the absence of a pink orthopedic component

SIPMO 2019

The biennial Congress of the Italian Society of Oral Pathology and Medicine (SIPMO) is an International meeting dedicated to the growing diagnostic challenges in the oral pathology and medicine field. The III International and XV National edition will be a chance to discuss clinical conditions which are unusual, rare, or difficult to define. Many consolidated national and international research groups will be involved in the debate and discussion through special guest lecturers, academic dissertations, single clinical case presentations, posters, and degree thesis discussions. The SIPMO Congress took place from the 17th to the 19th of October 2019 in Bari (Italy), and the enclosed copy of Proceedings is a non-exhaustive collection of abstracts from the SIPMO 2019 contributions

Stanozolol promotes osteogenic gene expression and apposition of bone mineral in vitro

Stanozolol (ST) is a synthetic androgen with high anabolic potential. Although it is known that androgens play a positive role in bone metabolism, ST action on bone cells has not been sufficiently tested to support its clinical use for bone augmentation procedures. Objective: This study aimed to assess the effects of ST on osteogenic activity and gene expression in SaOS-2 cells. Material and Methods: SaOS-2 deposition of mineralizing matrix in response to increasing doses of ST (0-1000 nM) was evaluated through Alizarin Red S and Calcein Green staining techniques at 6, 12 and 24 days. Gene expression of runt-related transcription factor 2 (RUNX2), vitamin D receptor (VDR), osteopontin (SPP1) and osteonectin (ON) was analyzed by RT-PCR. Results: ST significantly influenced SaOS-2 osteogenic activity: stainings showed the presence of rounded calcified nodules, which increased both in number and in size over time and depending on ST dose. RT-PCR highlighted ST modulation of genes related to osteogenic differentiation. Conclusions: This study provided encouraging results, showing ST promoted the osteogenic commitment of SaOS-2 cells. Further studies are required to validate these data in primary osteoblasts and to investigate ST molecular pathway of action

Chitosan-based scaffold modified with D-(+) raffinose for cartilage repair: an in vivo study

BackgroundOsteochondral defects significantly affect patients¿ quality of life and represent challenging tissue lesions, because of the poor regenerative capacity of cartilage. Tissue engineering has long sought to promote cartilage repair, by employing artificial scaffolds to enhance cell capacity to deposit new cartilage. An ideal biomaterial should closely mimic the natural environment of the tissue, to promote scaffold colonization, cell differentiation and the maintenance of a differentiated cellular phenotype. The present study evaluated chitosan scaffolds enriched with D-(+) raffinose in osteochondral defects in rabbits. Cartilage defects were created in distal femurs, both on the condyle and on the trochlea, and were left untreated or received a chitosan scaffold. The animals were sacrificed after 2 or 4 weeks, and samples were analysed microscopically.ResultsThe retrieved implants were surrounded by a fibrous capsule and contained a noticeable inflammatory infiltrate. No hyaline cartilage was formed in the defects. Although defect closure reached approximately 100% in the control group after 4 weeks, defects did not completely heal when filled with chitosan. In these samples, the lesion contained granulation tissue at 2 weeks, which was then replaced by fibrous connective tissue by week 4. Noteworthy, chitosan never appeared to be integrated in the surrounding cartilage.ConclusionsIn conclusion, the present study highlights the limits of D-(+) raffinose-enriched chitosan for cartilage regeneration and offers useful information for further development of this material for tissue repair

Aptamer-Mediated Selective Protein Affinity to Improve Scaffold Biocompatibility

Protein adsorption on surfaces occurs shortly after scaffold insertion. This process is of pivotal importance to achieve therapeutic success in tissue engineering (TE), and favorable proteins should be adsorbed at the interface without unfolding to preserve their structure and function. Protein misfolding at the interface is a common phenomenon, which can impair cell adhesion and scaffold colonization. Many efforts have been done to improve scaffold biocompatibility by ameliorating protein adsorption, but with poor results. In the present chapter, we propose the use of a novel class of molecules, aptamers, to improve scaffold biocompatibility. Aptamers are small, single stranded oligonucleotides, which specifically bind to a target molecule: they work as antibodies, but without many of the drawbacks associated to the use of antibodies. We propose to immobilize aptamers on scaffolds to retain specific proteins, acting as docking points to guide cell activity. In particular, we show the results obtained by enriching different polymeric scaffolds with aptamers against human fibronectin, a naturally abundant protein in tissues, which plays a pivotal role in cell adhesion. We demonstrate that scaffold enrichment with aptamers lead to a better colonization of the substrate from cells. The results we obtained pave the way to the possibility of further investigating the role of aptamers as useful molecules to improve scaffold biocompatibility in the contest of tissue engineering