Fast Shape Research Articles

A fast 3D shape measurement method based on sinusoidal and triangular fringe projection

Existing methods to measure 3D shape of complex object involve processing more than six captured images to obtain the absolute phase, which limit the measurement speed. This paper presents two sinusoidal fringes and two triangular wave fringes which is used to measure 3D shape of complex object. The two-step phase-shifting sinusoidal fringes and two-step phase-shifting triangular wave fringes are calculated to obtain the wrapped phase, and then the two-step phase-shifting triangular wave fringes are used to determine the fringe order. Due to decrease the number of projection fringes, the speed of measurement increases. The triangular wave fringe carries more information of the object than linear increasing/decreasing ramp fringe in the actual measurement, more noise in the base phase to be overcome, thus improving the measurement accuracy. The benefits can be widely applied in high-speed, real-time 3D measurement of complex shape. Experimental results have demonstrated that the proposed method is simple, but effective.

How to Size ASDs for Percutaneous Closure.

Percutaneous closure is the treatment of choice for secundum-type atrial septal defects (ASD). Balloon sizing (BS) has been the method of choice for deciding on device size. Improved 2D- and 3D-transesophageal echocardiographic (TEE) imaging challenged the necessity of BS. Balloon sizing was performed with two additional techniques to measure the stretched dimension of the ASD. The 1st method uses a stiff guide wire which stretches the ASD and 2D TEE. The second technique uses 3D TEE. Two hundred and thirty-six patients with minimum 1-year follow-up were enrolled. The population was classified into three groups: BS (group 1) n=90, 2D-TEE (group 2) n=87, and 3D-TEE (group 3) n=59. All groups showed a distinct correlation between the maximum baseline dimensions and the device size (R=0.821). The relative expansion rate did not differ between BS and 3D-TEE. Group 2 (2D-TEE) showed a significantly lower expansion rate. Procedural success and complications did not differ statistically between the 3 groups. 2D TEE sizing was the simplest method without loss of accuracy. 3D sizing offers the advantage of accurate and fast shape assessment, but resulted in more undersizing. Accurate sizing of ASDs with a floppy septum remains a challenge.

On the origin of shape fluctuations of the cell nucleus.

The nuclear envelope (NE) presents a physical boundary between the cytoplasm and the nucleoplasm, sandwiched in between two highly active systems inside the cell: cytoskeleton and chromatin. NE defines the shape and size of the cell nucleus, which increases during the cell cycle, accommodating for chromosome decondensation followed by genome duplication. In this work, we study nuclear shape fluctuations at short time scales of seconds in human cells. Using spinning disk confocal microscopy, we observe fast fluctuations of the NE, visualized by fluorescently labeled lamin A, and of the chromatin globule surface (CGS) underneath the NE, visualized by fluorescently labeled histone H2B. Our findings reveal that fluctuation amplitudes of both CGS and NE monotonously decrease during the cell cycle, serving as a reliable cell cycle stage indicator. Remarkably, we find that, while CGS and NE typically fluctuate in phase, they do exhibit localized regions of out-of-phase motion, which lead to separation of NE and CGS. To explore the mechanism behind these shape fluctuations, we use biochemical perturbations. We find the shape fluctuations of CGS and NE to be both thermally and actively driven, the latter caused by forces from chromatin and cytoskeleton. Such undulations might affect gene regulation as well as contribute to the anomalously high rates of nuclear transport by, e.g., stirring of molecules next to NE, or increasing flux of molecules through the nuclear pores.

A fast water-induced shape memory polymer based on hydroxyethyl cellulose/graphene oxide composites

Herein, a fast water responsive shape memory polymer composites based on hydroxyethyl cellulose (HEC) has been fabricated by crosslinking with graphene oxide (GO) and citric acid (CA). The swelling behavior, mechanical properties, micro-topography, thermal stability, as well as water and moisture induced shape memory performance of this composite were all fully investigated to demonstrate its functions. After crosslinking with GO and CA, the composite exhibited excellent mechanical properties with tensile strength over 100MPa, which was nearly 4 times higher than pure HEC. Moreover, the pre-deformed composite was able to fully recover to its original shape in aqueous environment, which not only quickly happened in water (14s), but also occurred in wet air with relative humidity about 70 within only 5min. With such outstanding properties, we envisage that this composite could play a significant role in developing new generations of water responsive sensors, actuators and biomedical devices.

Application of optical image analysis to the assessment of pore space evolution after CO2 injection in sandstones. A case study

This paper presents the application of an automated image processing method for detection and analysis of pores in thin section petrographic microscopy (optical porosity). The technique is applied to pore size distribution and pore shape parameter measurements on Spanish sandstone samples before and after their exposure to CO2 under supercritical conditions (SC). The presented optical image analysis (OIA) protocol allows fast, low-cost, effective and reproducible pore size and shape quantification and comparative study in 2D. The images are acquired using a high-resolution scanner (HRS) at 6.35 μm/pixel optical resolution, providing thus preliminary data for further, more detailed studies. After the definition of the pore space, individual pores and pore throats were identified. On the segmented optical pores, parameters such as area, feret diameters, roundness, pore aspect and pore throat diameter were calculated using Fiji software. The results were used for statistical analysis and for the construction of pore size distribution curves. Quantitative analysis with the OIA-HRS method facilitated the characterization of the samples and a preliminary approximation of the CO2-rock interactions at laboratory scale.

Linearized spectrum correlation analysis for line emission measurements.

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

Slide-ring shape memory polymers with movable cross-links

The development of shape memory materials to achieve recoverable high-strain capacities at high concentration of the crosslinker is still a great challenge due to their mutual exclusiveness. Here, slide-ring shape memory polymers (SMPs) with movable cross-links were prepared by varying the amount of the polyrotaxane cross-linkers. The slide-ring SMPs not only exhibit a combination of high strength and toughness, but also outstanding recoverable high-strain capacities and fast shape recovery. The elongation of the slide-ring SMPs at 1mol% crosslinker was as high as 881%, closer to physically cross-linked SMPs. As the growing deformation strain from 100% to 800%, the slide-ring SMPs still showed excellent shape memory performance with >90% shape fixity and shape recovery. The comparative analysis among movable cross-linking, chemical cross-linking and physical cross-linking SMPs in a different way revealed that the sliding effect of the polyrotaxane cross-linking is responsible for outstanding recoverable high-strain capacities of slide-ring SMPs. This design may provide a promising strategy for brittle shape memory materials to obtain high-strain capacities, such as epoxy resin and polylactic acid.

Fabricating fast triggered electro-active shape memory graphite/silver nanowires/epoxy resin composite from polymer template

In recent years shape-memory polymers have been under intense investigation due to their unique mechanical, thermal, and electrical properties that could potentially make them extremely valuable in numerous engineering applications. In this manuscript, we report a polymer-template-assisted assembly manufacturing strategy used to fabricate graphite/silver nanowires/epoxy resin (PGSE) composite. In the proposed method, the porous polymer foams work as the skeleton by forming three-dimensional graphite structure, whereas the silver nanowires act as the continuous conductive network. Preliminary testing on hybrid foams after vacuum infusion showed high electrical conductivity and excellent thermal stability. Furthermore, the composites were found to recover their original shape within 60 seconds from the application of a 0.8 V mm−1 electric field. Notably, the reported shape-memory polymer composites are manufactured with readily-available raw materials, they are fast to manufacture, and are shape-controlled.

Smooth shapes with spherical topology: Beyond traditional modeling, efficient deformation, and interaction

Existing shape models with spherical topology are typically designed either in the discrete domain using interpolating polygon meshes or in the continuous domain using smooth but non-interpolating schemes such as subdivision or NURBS. Both polygon models and subdivision methods require a large number of parameters to model smooth surfaces. NURBS need fewer parameters but have a complicated rational expression and non-uniform shifts in their formulation. We present a new method to construct deformable closed surfaces, which includes exact spheres, by combining the best of two worlds: a smooth, interpolating model with a continuously varying tangent plane and well-defined curvature at every point on the surface. Our formulation is considerably simpler than NURBS and requires fewer parameters than polygon meshes. We demonstrate the generality of our method with applications including intuitive user-interactive shape modeling, continuous surface deformation, shape morphing, reconstruction of shapes from parameterized point clouds, and fast iterative shape optimization for image segmentation. Comparisons with discrete methods and non-interpolating approaches highlight the advantages of our framework.

THE PARALLEL IMPLEMENTATION OF ALGORITHMS FOR FINDING THE REFLECTION SYMMETRY OF THE BINARY IMAGES

Abstract. In this paper, we investigate the exact method of searching an axis of binary image symmetry, based on brute-force search among all potential symmetry axes. As a measure of symmetry, we use the set-theoretic Jaccard similarity applied to two subsets of pixels of the image which is divided by some axis. Brute-force search algorithm definitely finds the axis of approximate symmetry which could be considered as ground-truth, but it requires quite a lot of time to process each image. As a first step of our contribution we develop the parallel version of the brute-force algorithm. It allows us to process large image databases and obtain the desired axis of approximate symmetry for each shape in database. Experimental studies implemented on “Butterflies” and “Flavia” datasets have shown that the proposed algorithm takes several minutes per image to find a symmetry axis. However, in case of real-world applications we need computational efficiency which allows solving the task of symmetry axis search in real or quasi-real time. So, for the task of fast shape symmetry calculation on the common multicore PC we elaborated another parallel program, which based on the procedure suggested before in (Fedotova, 2016). That method takes as an initial axis the axis obtained by superfast comparison of two skeleton primitive sub-chains. This process takes about 0.5 sec on the common PC, it is considerably faster than any of the optimized brute-force methods including ones implemented in supercomputer. In our experiments for 70 percent of cases the found axis coincides with the ground-truth one absolutely, and for the rest of cases it is very close to the ground-truth.

Precise shape matching of large shape datasets using hybrid approach

Precise and fast shape matching and retrieval from very large datasets is a challenging task because of the existence of many distortions such as noise, occlusion and affine distortions. In this paper, we aim to propose a time-saving and effective shape matching and retrieval framework, that employs pruning which will enable online shape retrieval from extremely large datasets. First, using a hierarchical tree-based structure supporting parallel processing and efficient feature descriptors, irrelevant shapes are pruned and a subset of shapes relevant to the query is selected, then using more sophisticated feature descriptors, accurate retrieval is performed. Contour representation of an object is considered as most significant visual shape similarity measure by the humans. Using boundary information, we generate two simplified and efficient feature descriptors for fast pruning, and a sophisticated feature descriptor for effective and accurate retrieval. Tests performed on standard datasets unveil that the proposed technique is computationally more efficient than the state-of-the-art techniques while maintaining comparable matching and retrieval performance. Its performance is scalable for huge datasets and is robust against affine transformations, articulations and occlusion.

Active tactile exploration with uncertainty and travel cost for fast shape estimation of unknown objects

In this paper, active tactile exploration for object shape estimation is explored. A prior work suggested to touch the most uncertain part of the estimated shape for minimizing the required number of touches. In this paper, it is pointed out that it may not be the best approach for fast estimation. We propose a novel criterion in active touch point selection for fast estimation, which considers both uncertainty of shape estimation and travel cost to touch. Our method employs a Gaussian process implicit surface model to learn the object shape from tactile information, which allows us to evaluate the uncertainty of the shape estimation with an analytic form. To estimate the travel costs for all the touch candidates, our method utilizes a computationally-efficient graph-based path planning method based on stochastic optimal control theory. Simulations with 2D and 3D objects and real-robot experiments with a 7DOF robot arm and a single finger device equipped with a tactile sensor are conducted. Experimental results verify the effectiveness of our method for fast tactile object shape estimation as compared to passive exploration and active exploration that touches the most uncertain part of the estimated shape.

Think locally, fit globally: Robust and fast 3D shape matching via adaptive algebraic fitting

In this paper, we propose a novel 3D free form surface matching method based on a novel key-point detector and a novel feature descriptor. The proposed detector is based on algebraic surface fitting. By global smooth fitting, our detector achieved high computational efficiency and robustness against non-rigid deformations. For the feature descriptor, we provide algorithms to compute 3D critical net which generates a meaningful structure on standalone local key-points. The scale invariant and deformation robust Dual Spin Image descriptor is provided based on the 3D critical net. Our method is proved by solid mathematics. Intensive quantitative experiments demonstrate the robustness, efficiency and accuracy of the proposed method.

The Partial Truncated Icosahedron Phoswich Detector Array: A Light Charged Particle Array for Pionic Fusion Measurements

The Partial Truncated Icosahedron (ParTI) phoswich detector array has been designed to detect charged pions and other light charged particles in pionic fusion reactions. The array has been constructed and characterized in a series of beam experiments. It is composed of 15 plastic/thalium-doped cesium iodide (CsI(Tl)) phoswich detector units arranged on the faces of a truncated icosahedron geometry which covers approximately 20% of the solid angle. The phoswich detectors have been shown to be capable of isotopic identification of Z = 1 and Z = 2 particles and elemental identification of at least up to Z = 3 using fast vs. slow pulse shape discrimination (PSD). Some advantages of employing digital electronics are discussed including identification of charged pions independent of PSD using their characteristic waveform response and selective event triggering using a muon decay trigger. A calibration method for the array is also described.

Three-dimensional shape measurement technique for shiny surfaces by adaptive pixel-wise projection intensity adjustment

Conventional methods based on analyses of the absolute gray levels of pixels in fringe pattern images are affected by the problems of image saturation, interreflection, and high sensitivity to noise when obtaining three-dimensional (3D) shape measurements of shiny surfaces. This study presents a robust, adaptive, and fast 3D shape measurement technique, which adaptively adjusts the pixel-wise intensity of the projected patterns, thus it avoids image saturation and has a high signal to noise ratio (SNR) during 3D shape measurement for shiny surfaces. Compared with previous time-consuming methods using multiple exposures and the projection of fringe patterns with multiple intensities, where a large number of fringe pattern images need to be captured, the proposed technique needs to capture far fewer pattern images for measurement. In addition, it can greatly reduce the time costs to obtain the optimal projection intensities by the fusion of uniform gray level patterns and coordinates mapping. Our experimental results demonstrate that the proposed technique can achieve highly accurate and efficient 3D shape measurement for shiny surfaces.

개량 Douglas-Peucker 알고리즘 기반 고속 Shape Matching 알고리즘

개량 Douglas-Peucker 알고리즘 기반 고속 Shape Matching 알고리즘

Fast shape recovery by changing the grafting ratio in polyurethane/montmorillonite–poly(methyl methacrylate) composites

The influence of the grafting ratio of PMMA on the shape memory effect was studied by synthesizing and characterizing fast recoverable polyurethane/montmorillonite–poly(methyl methacrylate) (PU/MMT–PMMA) composites. PMP3 with a grafting ratio=3 had the fastest recovery rate, 21.1° per second at 60 °C, whereas the recovery rates of PU and PU/MMT were 6.1 and 9.5° per second, respectively. All the samples recovered to the original shape in 3 s at 80 °C, while PMP3 displayed a much higher shape memory performance capacity than the other two specimens in 1 s.

Large Array Null Steering Using Compressed Sensing

In this letter, array null steering is formulated as a sparse recovery problem. In addition, a novel null steering scheme for large arrays by perturbing only a few elements is presented. To achieve this goal, compressed sensing (CS) is used to exploit the sparsity of the perturbed elements. The advantages of the proposed scheme are a significant reduction in hardware cost and lower power consumption, as well as less aging of the elements and faster response. Simulation results show that the CS-based method could be efficiently used to generate wide nulls using at least two elements. The interference rejection ratio achieved by the proposed method is 10–20 dB better than the existing solutions. The performance of different null generation methods in terms of peak-to-sidelobe ratio, pointing error, and beam-width is compared as well. The proposed algorithm is a prominent solution for the future 5G base stations, where a fast and low-cost beam shaping algorithm is required.

Graphene-crosslinked two-way reversible shape memory polyurethane nanocomposites with enhanced mechanical and electrical properties

Highly flexible, conductive, and two-way reversible shape memory polyurethane nanocomposites were prepared with the in situ synthesized method, containing different graphene nanosheet contents ranging from 1.0 to 8.0 wt%. The dispersion of the nanocomposites in the polymer was monitored by scanning electron microscopy and thermal properties, mechanical properties, electrical properties, shape memory properties were comparatively investigated. The results showed that the nanocomposite was more stable when the content of graphene is 2 wt% in the crosslinked network structure. In comparison to pristine polyurethane, the graphene crosslinked polyurethane composite exhibited better thermostability, breaking stress, and exceptional elongation-at-break. The resulting composite exhibited 93 % shape fixity, 95 % shape recovery of 2.0 % loading, and fast electroactive shape recovery rate. Moreover, the polymers also showed good reversible two-way shape memory behaviors, thus it could be a promising material for the fabrication of graphene-based actuating devices.

Silhouette Orientation Volumes for Efficient Fall Detection in Depth Videos.

A novel method to detect human falls in depth videos is presented in this paper. A fast and robust shape sequence descriptor, namely the Silhouette Orientation Volume (SOV), is used to represent actions and classify falls. The SOV descriptor provides high classification accuracy even with a combination of simple associated models, such as Bag-of-Words and the Naïve Bayes classifier. Experiments on the public SDU-Fall dataset show that this new approach achieves up to 91.89% fall detection accuracy with a single-view depth camera. The classification rate is about 5% higher than the results reported in the literature. An overall accuracy of 89.63% was obtained for the six-class action recognition, which is about 25% higher than the state of the art. Moreover, a perfect silhouette-based action recognition rate of 100% is achieved on the Weizmann action dataset.