516 research outputs found
Reconstruction of 3D faces by shape estimation and texture interpolation
This paper aims to address the ill-posed problem of reconstructing 3D faces from single 2D face images. An
extended Tikhonov regularization method is connected with the standard 3D morphable model in order to
reconstruct the 3D face shapes from a small set of 2D facial points. Further, by interpolating the input 2D
texture with the model texture and warping the interpolated texture to the reconstructed face shapes, 3D face
reconstruction is achieved. For the texture warping, the 2D face deformation has been learned from the model
texture using a set of facial landmarks. Our experimental results justify the robustness of the proposed approach
with respect to the reconstruction of realistic 3D face shapes
Adaptive face modelling for reconstructing 3D face shapes from single 2D images
Example-based statistical face models using principle component analysis (PCA) have been widely deployed for three-dimensional (3D) face reconstruction and face recognition. The two common factors that are generally concerned with such models are the size of the training dataset and the selection of different examples in the training set. The representational power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. The RP of the model can be increased by correspondingly increasing the number of training samples. In this contribution, a novel approach is proposed to increase the RP of the 3D face reconstruction model by deforming a set of examples in the training dataset. A PCA-based 3D face model is adapted for each new near frontal input face image to reconstruct the 3D face shape. Further an extended Tikhonov regularisation method has been
Reconstructing 3D face shapes from single 2D images using an adaptive deformation model
The Representational Power (RP) of an example-based model is its capability to depict a new 3D face for a given 2D face image. In this contribution, a novel approach is proposed to increase the RP of the 3D reconstruction PCA-based model by deforming a set of examples in the training dataset. By adding these deformed samples together with the original training samples we gain more RP. A 3D PCA-based model is adapted for each new input face image by deforming 3D faces in the training data set. This adapted model is used to reconstruct the 3D face shape for the given input 2D near frontal face image. Our experimental results justify that the proposed adaptive model considerably improves the RP of the conventional PCA-based model
Surface effects on nanowire transport: numerical investigation using the Boltzmann equation
A direct numerical solution of the steady-state Boltzmann equation in a
cylindrical geometry is reported. Finite-size effects are investigated in large
semiconducting nanowires using the relaxation-time approximation. A nanowire is
modelled as a combination of an interior with local transport parameters
identical to those in the bulk, and a finite surface region across whose width
the carrier density decays radially to zero. The roughness of the surface is
incorporated by using lower relaxation-times there than in the interior.
An argument supported by our numerical results challenges a commonly used
zero-width parametrization of the surface layer. In the non-degenerate limit,
appropriate for moderately doped semiconductors, a finite surface width model
does produce a positive longitudinal magneto-conductance, in agreement with
existing theory. However, the effect is seen to be quite small (a few per cent)
for realistic values of the wire parameters even at the highest practical
magnetic fields. Physical insights emerging from the results are discussed.Comment: 15 pages, 7 figure
A Conceptual Frame Work of Supply Chain Integration for Competitive Advantage
Growth as one of the key preconditions to survive in the market is forcing companies to compete on international markets and at the same time defend domestic market share from international competitors. The result of that is increased complexity of supply chains, pressure to decrease cost and improve service level. To cope with the complexity and increased customer requirements, active management of the supply chain is a prerequisite. As supply chain is a network of three or more entities directly involved in the upstream and downstream flows of products, services, finance and information from a source to a customer, management of it is a complex task.
There is significant evidence from literature that the effective implementation of integrated supply chain management (SCM) has the potential to generate significant improvements in the performance of firms. The higher levels of SCM practice can lead to enhanced competitive advantage and improved organizational performance. In order to achieve efficient supply chain integration for the processes or activities; the organizations should recognize and understand all the integration challenges of supply chain.
The aim of this paper is to investigate previous research studying the relationship between supply chain integration and performance and understand the importance of supply chain integration for competitive position of organization. Address the challenges encountered in integration of supply chain. Propose a conceptual frame work to reap the potential benefits of effective supply chain integration
New primary renal diagnosis codes for the ERA-EDTA
The European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry has produced a new set of primary renal diagnosis (PRD) codes that are intended for use by affiliated registries. It is designed specifically for use in renal centres and registries but is aligned with international coding standards supported by the WHO (International Classification of Diseases) and the International Health Terminology Standards Development Organization (SNOMED Clinical Terms). It is available as supplementary material to this paper and free on the internet for non-commercial, clinical, quality improvement and research use, and by agreement with the ERA-EDTA Registry for use by commercial organizations. Conversion between the old and the new PRD codes is possible. The new codes are very flexible and will be actively managed to keep them up-to-date and to ensure that renal medicine can remain at the forefront of the electronic revolution in medicine, epidemiology research and the use of decision support systems to improve the care of patients
Phase Dependent Thermopower in Andreev Interferometers
We report measurements of the thermopower S of mesoscopic Andreev
interferometers, which are hybrid loops with one arm fabricated from a
superconductor (Al), and one arm from a normal metal (Au). S depends on the
phase of electrons in the interferometer, oscillating as a function of magnetic
flux with a period of one flux quantum (= h/2e). The magnitude of S increases
as the temperature T is lowered, reaching a maximum around T = 0.14 K, and
decreases at lower temperatures. The symmetry of S oscillations with respect to
magnetic flux depends on the topology of the sample.Comment: 4 pages, 4 figure
Growth analysis and curcumin content of long, medium and short duration turmeric (Curcuma longa L.) genotypes
Six turmeric (Curcuma longa) genotypes, two genotypes each from long (Armoor andDuggirala), medium (CLI-317 and CLI-330) and short (PCT-13 and PCT-14) duration wereevaluated at Jagtial (Andhra Pradesh). Long duration genotypes accumulated more drymatter and maintained leaf area index, chlorophyll content and cumulative growth rate forlonger period up to 210 days, resulting in higher yield and curing percentage over mediumand short duration genotypes. The long duration genotype Duggirala produced highestfresh rhizome yield (168 g plant-1) and Armoor had highest curing percentage (20.26).Curcumin content was higher in short duration genotypes over medium and long durationgenotypes. Maximum curcumin content was recorded in short duration genotype PCT-14(4.06 %).
 
Feasibility of Model-Assisted Probability of Detection Principles for Structural Health Monitoring Systems Based on Guided Waves for Fiber-Reinforced Composites
In many industrial sectors, structural health monitoring (SHM) is considered as an addition to nondestructive testing (NDT) that can reduce maintenance effort during the lifetime of a technical facility, structural component, or vehicle. A large number of SHM methods are based on ultrasonic waves, whose properties change depending on structural health. However, the wide application of SHM systems is limited due to the lack of suitable methods to assess their reliability. The evaluation of the system performance usually refers to the determination of the probability of detection (POD) of a test procedure. Up until now, only a few limited methods exist to evaluate the POD of SHM systems, which prevents them from being standardized and widely accepted in the industry. The biggest hurdle concerning the POD calculation is the large number of samples needed. A POD analysis requires data from numerous identical structures with integrated SHM systems. Each structure is then damaged at different locations and with various degrees of severity. All of these are connected to high costs. Therefore, one possible way to tackle this problem is to perform computer-aided investigations. In this work, the POD assessment procedure established in NDT according to the Berens model is adapted to guided wave-based SHM systems. The approach implemented here is based on solely computer-aided investigations. After efficient modeling of wave propagation phenomena across an automotive component made of a carbon-fiber-reinforced composite, the POD curves are extracted. Finally, the novel concept of a POD map is introduced to look into the effect of damage position on system reliability
Genetic divergence in germplasm collections of turmeric (Curcuma longa L.)
Fifty four turmeric (Curcuma longa) cultivars were evaluated at Jagtial (Andhra Pradesh) by subjecting to D2 statistic to assess the genetic diversity available in the cultivars. The D2 analysis showed wide diversity among the cultivars and they were grouped into six clusters. Inter-cluster distance values also showed wide genetic divergence among the cultivars. Based on cluster-mean values, the cultivars PTS-38 and Duggirala in cluster I (high cured yield), PCT-5 and PCT-8 in cluster III (high curcumin, essential oil and oleoresin contents) and PCT-13, PCT-14 and PCT-10 in cluster IV (short duration, medium yield with good curcumin content) were identified as potential parents for future breeding programmes.
 
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