Shape recovery using high dynamic range images

An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.

Relationship between Colored Microstructure under Polarized Light and Shape Recovery Characteristics on the Thermomechanical Cycled CuAlNi Single Crystals

The paper studied the relationship between microstructure and shape recovery characteristics by using colored microstructure analysis under polarized light on the thermomechanical cycled CuAlNi single crystals. The two-way shape memory effect in quenched thin bar resulted from the preferential formation/extinction of martensite variant due to the internal quench stress, and the variant was formed at an angle of about 45 deg. with the tension direction ([001] of the βphase). Initial thermomechanical cycling under relatively low stress single variant stress-induced martensite was formed at an angle of 45 deg. with the tension and its morphology was a lath of parallel twins. More than one group of variants were formed after several training cycles and such variants also caused tilting of some thermally formed accommodated martensite. By overheating the trained sample containing stabilized multi-variants of stress-induced martensite, very coarse martensite structure with a strong asymmetry was produced, which caused the reverse two-way shape memory effect.

Shape Recovery of Elastic Capsules from Shear Flow Induced Deformation

Red blood cells undergo substantial shape changes in vivo.Modeled as a viscoelastic capsule,their deformation and equilibrium behavior has been extensively studied.We consider how 2D capsules recover their shape,after having been deformed to’equilibrium’behavior by shear flow.The fluid-structure interaction is modeled using the multiple-relaxation time lattice Boltzmann(LBM)and immersed boundary(IBM)methods.Characterizing the capsule’s shape recovery with the Taylor deformation parameter,we find that a single exponential decay model suffices to describe the recovery of a circular capsule.However,for biconcave capsules whose equilibrium behaviors are tank-treading and tumbling,we posit a two-part recovery,modeled with a pair of exponential decay functions.We consider how these two recovery modes depend on the capsule’s shear elasticity,membrane viscosity,and bending stiffness,along with the ratio of the viscosity of the fluid inside the capsule to the ambient fluid viscosity.We find that the initial recovery mode for a tank-treading biconcave capsule is dominated by shear elasticity and membrane viscosity.On the other hand,the latter recovery mode for both tumbling and tank-treading capsules,depends clearly on shear elasticity,bending stiffness,and the viscosity ratio.

Recovery Stress in a Ni-Ti-Nb Shape Memory Alloy with Wide Transformation Hysteresis

The effect of deformation on recovery stress of Ni144.7Ti46.3Nb9 alloy has been studjed using tensile test at various temperatures and TEM observation. It ls shown that the recovery stress increases with jncreasing total strain ET and reaches a maximum value (max) as ET= 9% but the maximum recov erV strain of the alloy is only about 4.6%. This is different from that of Ti-Ni binary alloy in which is obtained usually at maximum recovery strain and the reason of the difference is dis Cussed. Deformation temperature Td has a little effect on recovery stress when Td is less than Ms However, recovery stress decreases sharply when Td is higher than M, and lowers approximately down to zero near Msσ

EFFECT OF QUENCHING TEMPERATURE ON SHAPE MEMORY EFFECT OF Fe-18Mn -5Si-8Cr-4Ni ALLOY

The effects of quenching temperature on shape memory effect and microstructure of Fe 18Mn 5Si 8Cr 4Ni shape memory alloy have been studied. The results show that both the shape recovery ratio and the recovery strain increased as quenching temperature increased, the amount of stress induced ε martensite in the process of cold work decreased with the increase of quenching temperature, the shape recovery ratio and the recovery strain reached maximum at 650℃, and then decreased rapidly with the further increase of quenching temperature,the stress induced ε martensite wholly disappeared at 1023K. But when the quenching temperature is higher than 1023K, the further increase of quenching temperature had little effect on shape recovery ratio, the amount and size of thermal induced ε martensite would increased with the further increase in quenching temperature. The shape memory effect can be improved by the moderate amount of pre exist ε martensite in the matrix before deforming.

Recent advances in multifunctional shape memory photonic crystals and practical applications

Shape memory photonic crystals(SMPCs)are smart composite materials with changeable structural color integrated by shape memory polymer and photonic crystals.SMPC can produce one or more temporary shapes through nanoscale deformation,memorizing current states.SMPC can be recovered to their original shapes or some intermediate states under external stimuli,accompanied by the variation of structural color.As porous carriers with built-in sensing properties,SMPCs promoted the interdisciplinary development of nanophotonic technology in materials science,environmental engineering,biomedicine,chemical engineering,and mechanics.Herein,the recent progress on multifunctional SMPCs and practical applications,including traditional and cold programmable SMPCs,is summarized and discussed.The primary concern is shape programming at the nanoscale that has demonstrated numerous attractive functions,including smart sensing,ink-free printing,solvent detection,reprogrammable gradient wetting,and controllable bubble transportation,under variations of the surface nanostructure.It aims to figure out the nanoscale shape memory effects on structural color conversion and additional performance,inspiring the fabrication of the next generation of SMPCs.Finally,perspectives on future research directions and applications are also presented.It is believed that multifunctional SMPCs are powerful nanophotonic tools for the interdisciplinary development of numerous disciplines in the future.

Binary Tomography Reconstruction with Limited-Data by a Convex Level-Set Method

This paper proposes a new level-set-based shape recovery approach that can be applied to a wide range of binary tomography reconstructions.In this technique,we derive generic evolution equations for shape reconstruction in terms of the underlying level-set parameters.We show that using the appropriate basis function to parameterize the level-set function results in an optimization problem with a small number of parameters,which overcomes many of the problems associated with the traditional level-set approach.More concretely,in this paper,we use Gaussian functions as a basis function placed at sparse grid points to represent the parametric level-set function and provide more flexibility in the binary representation of the reconstructed image.In addition,we suggest a convex optimization method that can overcome the problem of the local minimum of the cost function by successfully recovering the coefficients of the basis function.Finally,we illustrate the performance of the proposed method using synthetic images and real X-ray CT projection data.We show that the proposed reconstruction method compares favorably to various state-of-the-art reconstruction techniques for limited-data tomography,and it is also relatively stable in the presence of modest amounts of noise.Furthermore,the shape representation using a compact Gaussian radial basis function works well.

Active Contours and Mumford-Shah Segmentation Based on Level Sets

This paper is to detect regions (objects) boundaries, also to isolate and extract individual components from a medical image. This can be done using an active contours to detect regions in a given image, based on techniques of curve evolution, Mumford Shah functional for segmentation and level sets. The paper classified the images into different intensity regions based on Markov random field, then detected regions whose boundaries are not necessarily defined by gradient by minimizing an energy of Mumford Shah functional for segmentation which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a mean curvature flow like evolving the active contour, which will stop on the desired boundary. The stopping term does not depend on the gradient of the image, as in the classical active contour and the initial curve of level set can be anywhere in the image, and interior contours are automatically detected. The final image segmentation is one closed boundary per actual region in the image.

Cold-induced shape memory hydrogels for strong and programmable artificial muscles

Thermo-responsive shape memory hydrogels generally achieve shape fixation at low temperatures,and shape recovery at high temperatures.However,these hydrogels usually suffer from poor mechanical properties.Herein,we present a unique poly(acrylic acid)/calcium acetate shape memory hydrogel with cold-induced shape recovery performances as ultrastrong artificial muscles.Since the acetate groups could form aggregate at high temperatures and thus induce the association of the hydrogel network,the hydrogel can be fixed into a temporary shape upon heating and recover to its original shape in a cold environment.Moreover,a programmable shape recovery process is realized by adjusting the shape fixing time.In addition,the unique shape memory process enables the application demonstration as bio-inspired artificial muscles with an ultrahigh work density of45.2 kJ m^(-3),higher than that of biological muscles(~8 kJ m^(-3)).

Preliminary design and analysis of a cubic deployable support structure based on shape memory polymer composite

The deployable structures based on shape memory polymer com-posites(SMPCs)have been developed for its unique properties,such as high reliability,low-cost,lightweight,and self-deployment without complex mechanical devices compared with traditional deployable structures.In order to increase the inflatable structure system’s robustness and light the weight of it,a cubic deployable support structure based on SMPC is designed and analyzed pre-liminarily.The cubic deployable support structure based on SMPC consists of four dependent spatial cages,each spatial cage is composed of 12 three-longeron SMPC truss booms and end con-nections.The shape recovery of arc-shaped deployable laminates drive the three-longeron SMPC truss booms to unfold,thus realize the expansion of the deployable support structure.The concept and operation of the cubic deployable support structure are described in detail.A series of experiments are performed on the three-longeron deployable laminates unit and the simplified cubic deployable support structure to investigate the shape recovery behavior in the deployment process.Results indicate that the cubic deployable support structure has a high deployment-tgo-stowage volume ratio and can achieve self-deployment,package,and deploy without complex mechanical devices.

A Parallel Voting Scheme for Aspect Recovery

Recently, a qualitative approach was proposed for 3-D shape recovery based on a hybrid object representation[1]. In this approach, aspect recovery is the most important stage which binds regions in the image into meaningful aspects to support 3-D primitive recovery. There is no known polynondal time algo-rithm to solve this problem. The previous approach dealt with this problem by using a heuristic method based on the conditional probability. Unlike the previous method, this paper presents a novel parallel voting scheme to conquer the problem for efficiency. For this purpose) the previous global aspect rep-resentation is replaced with a distributed representation of aspects. Based on this representation, a three-layer parallel voting network for aspect recovery is proposed. For evaluating likelihood, a continuous Hopfield net is employed so that all aspect coverings in decreasing order of likelihood can be enumerated.The paper describes this method in detail and demonstrates its usefulness with simulation.

Mesh-Based Semi-Calibrated Photometric Stereo with Near Quasi Point Lights

Non-uniformity of light sources is one of the inevitable error factors causing poor shape recoveryaccuracy of photometric stereo methods under close-range lighting with quasi point lights. Semi-calibrated photometricstereo methods are required to avoid repeated, tedious and impractical photometric calibration. In thispaper, two simple, concise but effective mesh-based semi-calibrated photometric stereo methods are proposed.The proposed methods extend the traditional mesh-based photometric stereo methods and further allow joint andaccurate estimation of normals and non-uniform light intensities by alternatively updating normals, depth mapsand intensities. Extensive experiments are conducted to validate the effectiveness and robustness of the proposedalgorithms. Even under extremely severe non-uniform lighting, the proposed methods can still suppress the errorand improve the shape recovery accuracy by up to 65.6% in real-world experiments.

Anelasticity of twinned CuO nanowires

The mechanical behavior of CuO nanowires （NWs） was investigated by in situ transmission electron microscopy. During compression, the NWs exhibited high bending capabilities associated with high mechanical stress. Interestingly, anelasticity was consistently observed after stress release. Further investigations indicate that the anelasticity is intrinsic to the CuO NWs, although electron- beam irradiation was proved capable of accelerating the shape recovery. A mechanism based on the cooperative motion of twin-associated atoms is proposed to account for this phenomenon. The results provide insight into the mechanical properties of CuO NWs, which are promising materials for nanoscale damping systems.

Edge-preserving image decomposition via joint weighted least squares

Recent years have witnessed the emergence of image decomposition techniques which effectively separate an image into a piecewise smooth base layer and several residual detail layers. However, the intricacy of detail patterns in some cases may result in side-effects including remnant textures, wronglysmoothed edges, and distorted appearance. We introduce a new way to construct an edge-preserving image decomposition with properties of detail smoothing, edge retention, and shape fitting. Our method has three main steps: suppressing highcontrast details via a windowed variation similarity measure, detecting salient edges to produce an edgeguided image, and fitting the original shape using a weighted least squares framework. Experimental results indicate that the proposed approach can appropriately smooth non-edge regions even when textures and structures are similar in scale. The effectiveness of our approach is demonstrated in the contexts of detail manipulation, HDR tone mapping,and image abstraction.

3D corrective nose reconstruction from a single image

There is a steadily growing range of applications that can benefit from facial reconstruction techniques,leading to an increasing demand for reconstruction of high-quality 3D face models.While it is an important expressive part of the human face,the nose has received less attention than other expressive regions in the face reconstruction literature.When applying existing reconstruction methods to facial images,the reconstructed nose models are often inconsistent with the desired shape and expression.In this paper,we propose a coarse-to-fine 3D nose reconstruction and correction pipeline to build a nose model from a single image,where 3D and 2D nose curve correspondences are adaptively updated and refined.We first correct the reconstruction result coarsely using constraints of 3D-2D sparse landmark correspondences,and then heuristically update a dense 3D-2D curve correspondence based on the coarsely corrected result.A final refinement step is performed to correct the shape based on the updated 3D-2D dense curve constraints.Experimental results show the advantages of our method for 3D nose reconstruction over existing methods.