Stochastic Refinement of the Visual Hull to Satisfy Photometric and Silhouette Consistency Constraints

An iterative method for reconstructing a 3D polygonal mesh and color texture map from multiple views of an object is presented. In each iteration, the method first estimates a texture map given the current shape estimate. The texture map and its associated residual error image are obtained via maximum a posteriori estimation and reprojection of the multiple views into texture space. Next, the surface shape is adjusted to minimize residual error in texture space. The surface is deformed towards a photometrically-consistent solution via a series of 1D epipolar searches at randomly selected surface points. The texture space formulation has improved computational complexity over standard image-based error approaches, and allows computation of the reprojection error and uncertainty for any point on the surface. Moreover, shape adjustments can be constrained such that the recovered model's silhouette matches those of the input images. Experiments with real world imagery demonstrate the validity of the approach.

Color Region Grouping and Shape Recognition with Deformable Models

A new deformable shape-based method for color region segmentation is described. The method includes two stages: over-segmentation using a traditional color region segmentation algorithm, followed by deformable model-based region merging via grouping and hypothesis selection. During the second stage, region merging and object identification are executed simultaneously. A statistical shape model is used to estimate the likelihood of region groupings and model hypotheses. The prior distribution on deformation parameters is precomputed using principal component analysis over a training set of region groupings. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with similarly colored adjacent objects. Furthermore, the recovered parametric shape model can be used directly in object recognition and comparison. Experiments in segmentation and image retrieval are reported.

Retrieval by Shape Population: An Index Tree Approach

Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

Active Voodoo Dolls: A Vision Based Input Device for Nonrigid Control

A vision based technique for non-rigid control is presented that can be used for animation and video game applications. The user grasps a soft, squishable object in front of a camera that can be moved and deformed in order to specify motion. Active Blobs, a non-rigid tracking technique is used to recover the position, rotation and non-rigid deformations of the object. The resulting transformations can be applied to a texture mapped mesh, thus allowing the user to control it interactively. Our use of texture mapping hardware allows us to make the system responsive enough for interactive animation and video game character control.

Deformable Shape Detection and Description via Model-Based Region Grouping

A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with adjacent objects or shadows. The formulation can be used to group image regions based on any image homogeneity predicate; e.g., texture, color, or motion. The recovered shape models can be used directly in object recognition. Experiments with color imagery are reported.

Region Segmentation via Deformable Model-Guided Split and Merge

An improved method for deformable shape-based image segmentation is described. Image regions are merged together and/or split apart, based on their agreement with an a priori distribution on the global deformation parameters for a shape template. The quality of a candidate region merging is evaluated by a cost measure that includes: homogeneity of image properties within the combined region, degree of overlap with a deformed shape model, and a deformation likelihood term. Perceptually-motivated criteria are used to determine where/how to split regions, based on the local shape properties of the region group's bounding contour. A globally consistent interpretation is determined in part by the minimum description length principle. Experiments show that the model-based splitting strategy yields a significant improvement in segmention over a method that uses merging alone.

Latest development of the combinatorial model of nuclear level densities

The combinatorial model of nuclear level densities has now reached a level of accuracy comparable to that of the best global analytical expressions without suffering from the limits imposed by the statistical hypothesis on which the latter expressions rely. In particular, it provides, naturally, non-Gaussian spin distribution as well as non-equipartition of parities which are known to have an impact on cross section predictions at low energies [1, 2, 3]. Our previous global models developed in Refs. [1, 2] suffered from deficiencies, in particular in the way the collective effects - both vibrational and rotational - were treated. We have recently improved this treatment using simultaneously the single-particle levels and collective properties predicted by a newly derived Gogny interaction [4], therefore enabling a microscopic description of energy-dependent shell, pairing and deformation effects. In addition for deformed nuclei, the transition to sphericity is coherently taken into account on the basis of a temperature-dependent Hartree-Fock calculation which provides at each temperature the structure properties needed to build the level densities. This new method is described and shown to give promising results with respect to available experimental data.

Platinum nuclei: Concealed configuration mixing and shape coexistence

The role of configuration mixing in the Pt region is investigated. For this chain of isotopes, the nature of the ground state changes smoothly, being spherical around mass A~174 and A~192 and deformed around the midshell N=104 region. This has a dramatic effect on the systematics of the energy spectra as compared to the systematics in the Pb and Hg nuclei. Interacting boson model with configuration mixing calculations are presented for gyromagnetic factors, α-decay hindrance factors, and isotope shifts. The necessity of incorporating intruder configurations to obtain an accurate description of the latter properties becomes evident. © 2011 American Physical Society.

Dynamic fluid-structure interaction using finite volume unstructured mesh procedures

A three dimensional finite volume, unstructured mesh method for dynamic fluid-structure interation is described. The broad approach is conventional in that the fluid and structure are solved sequentially. The pressure and viscous stresses from the flow algorithm provide load conditions for the solid algorithm, whilst at the fluid structure interface the deformed structure provides boundary condition from the structure to the fluid. The structure algorithm also provides the necessary mesh adaptation for the flow field, the effect of which is accounted for in the flow algorithm. The procedures described in this work have several novel features, namely: * a single mesh covering the entire domain. * a Navier Stokes flow. * a single FV-UM discretisation approach for both the flow and solid mechanics procedures. * an implicit predictor-corrector version of the Newmark algorithm. * a single code embedding the whole strategy. The procedure is illustrated for a three dimensional loaded cantilever in fluid flow.

The role of plug design in determining wall thickness distribution in thermoforming

An experimental investigation has been carried out into the effects of changes in plug design on the wall thickness distribution of thermoformed products. Plugs were machined with a series of geometrical variations and their effects on the process were measured. The overall results show that the plug has a crucial role in controlling the wall thickness distribution in thermoforming. Larger plugs tend to distribute more material to the base of the product, but the introduction of a small sidewall taper, base radius, or a reduction in plug diameter tend to lead to more balanced distributions. However, larger changes in any of the variables tend to destroy these benefits. It has also been demonstrated that the frictional and thermal properties of the plug are important in determining the deformation response of the sheet material. There is a clear evidence of slip in the sheet during plug contact and, although the cooling effect of the plug appears to be minimal, cooling in the highly deformed regions away from the plug appears to be a significant factor.

Bond and Interfacial Properties of Reinforcement in Self-Compacting Concrete

This paper reports a study carried out to assess the impact of the use of self-compacting concrete (SCC) on bond and interfacial properties around steel reinforcement in practical concrete element. The pull-out tests were carried out to determine bond strength between reinforcing steel bar and concrete, and the depth-sensing nano-indentation technique was used to evaluate the elastic modulus and micro-strength of the interracial transition zone (ITZ) around steel reinforcement. The bond and interracial properties around deformed steel bars in different SCC mixes with strength grades of 35 MPa and 60 MPa (C35, C60) were examined together with those in conventional vibrated reference concrete with the same strength grades. The results showed that the maximum bond strength decreased when the diameter of the steel bar increased from 12 to 20 mm. The normalised bond strengths of the SCC mixes were found to be about 10-40% higher than those of the reference mixes for both bar diameters (12 and 20 mm). The study of the interfacial properties revealed that the elastic modulus and the micro-strength of the ITZ were lower on the bottom side of a horizontal steel bar than on the top side, particularly for the vibrated reference concrete. The difference of ITZ properties between top and bottom side of the horizontal steel bar appeared to be less pronounced for the SCC mixes than for the corresponding reference mixes.

Research strategies to improve honeybee health in Europe

Understanding the fundaments of colony losses and improving the status of colony health will require cross-cutting research initiatives including honeybee pathology, chemistry, genetics and apicultural extension. The 7th framework of the European Union requested research to empirically and experimentally fill knowledge gaps on honeybee pests and diseases, including 'Colony Collapse Disorder' and the impact of parasites, pathogens and pesticides on honeybee mortality. The interactions among these drivers of colony loss will be studied in different European regions, using experimental model systems including selected parasites (e. g. Nosema and Varroa mites), viruses (Deformed Wing Virus, Black Queen Cell Virus, Israeli Acute Paralysis Virus) and model pesticides (thiacloprid, tau-fluvalinate). Transcriptome analyses will be used to explore host-pathogen-pesticide interactions and identify novel genes for disease resistance. Special attention will be given to sublethal and chronic exposure to pesticides and will screen how apicultural practices affect colony health. Novel diagnostic screening methods and sustainable concepts for disease prevention will be developed resulting in new treatments and selection tools for resistant stock. Research initiatives will be linked to various national and international ongoing European, North-and South-American colony health monitoring and research programs, to ensure a global transfer of results to apicultural practice in the world community of beekeepers.

Microstructure and mechanical properties of low nickel maraging steel

Austenitization with lower temperature and intercritical annealing were introduced in the treatment of a maraging steel with a composition of Fe–12.94Ni–1.61Al–1.01Mo–0.23Nb (wt.%). Scanning electron microscopy was employed to study the microstructure after austenitization at 950 °C and intercritical annealing, followed by aging at 485 and 600 °C. X-ray diffraction (XRD) analysis was applied to evaluate the formation of retained or reverted austenite. Thermodynamic calculation was employed to calculate equilibrium phase mole fractions. Hardness and Charpy impact toughness of the steel were measured. Intercritical annealing treatments did not result in significant increase of hardness either before or after aging. The Charpy impact toughness of the alloy in aged condition was enhanced after austenitization at 950 °C. No austenite was observed in XRD. However, suspected reverted austenite was found after austenitization at 950 °C followed by aging at 600 °C for 4 h. Relationships among heat treatment, microstructure and mechanical properties are discussed.

Phase transformations in maraging steels

Research on the kinetics of precipitate formation and austenite reversion in maraging steels has received great attention due to their importance to steel properties. Judging from the literature in recent years, research into maraging steels has been very active, mainly extending to new types of steels, for new applications beyond the traditional strength requirements. This chapter provides an in-depth overview of the literature in this area. In addition, the kinetics of precipitate formation are analysed using the Johnson–Mehl–Avrami (JMA) theory.

Virtual Manufacturing of Composite Structures Applying Implicit and Explicit FE Techniques

Virtual manufacturing of composites can yield an initial early estimation of the induced residual thermal stresses that affect component fatigue life, and deformations that affect required tolerances for assembly. Based on these estimation, the designer can make early decisions, which can help in reducing cost, regarding changes in part design or material properties. In this paper, an approach is proposed to simulate the autoclave manufacturing technique for unidirectional composites. The proposed approach consists of three modules. The first module is a Thermochemical model to estimate temperature and the degree of cure distributions in the composite part during the cure cycle. The second and third modules are stress analysis using FE-Implicit and FE-Explicit respectively. User-material subroutine will be used to model the Viscoelastic properties of the material based on micromechanical theory. Estimated deformation of the composite part can be corrected during the autoclave process by modifying the process-tool design. The deformed composite surface is sent to CATIA for design modification of the process-tool.