Illumination Model Research Articles

Quantitative analysis of facial soft tissue using weighted cascade regression model applicable for facial plastic surgery

Localization of facial landmarks plays an important role in the measurement of facial metrics applicable for beauty analysis and facial plastic surgery. The first step in detecting facial landmarks is to estimate the face bounding box. Clinical images of patients' faces usually show intensity non-uniformity. These conditions cause common face detection algorithms do not perform well in face detection under varying illumination. To solve this problem, a modified fuzzy c-means (MFCM) algorithm is used under varying illumination modeling. The cascade regression method (CRM) has an appropriate performance in face alignment. This algorithm has two main drawbacks. (1) In the training phase, increasing the real data without considering normal data can lead to over-fitting. To solve this problem, a weighted CRM (WCRM) is presented. (2) In the test phase, using a mean shape causes the initial shape to be either near to or far from the face shape. To overcome this problem, a Procrustes-based analysis is presented. One of the most important steps in facial landmark localization is feature extraction. In this study, to increase detection accuracy of the cephalometric landmarks, local phase quantization (LPQ) is used for feature extraction in all three channels of RGB color space. Finally, the proposed algorithm is used to measure facial anthropometric metrics. Experimental results show that the proposed algorithm has a better performance in facial landmark localization than other compared algorithms.

Diagnostics from Polarization of Scattered Optical Light from Galactic Infrared Cirrus

We propose polarization of scattered optical light from intermediate Galactic latitude infrared cirrus as a new diagnostic to constrain models of interstellar dust and the anisotropic interstellar radiation field (aISRF). For single scattering by a sphere, with Mie scattering phase functions for intensity and polarized intensity for a dust model at a given wavelength (Sloan r and g bands), and with models of anisotropic illumination from the entire sky (represented in HEALPix), we develop the formalism for calculating useful summary parameters for an integrated flux nebula (IFN): the average of the phase function weighted by the illumination, polarization angle (ψ), and polarization fraction (p). To demonstrate the diagnostic discrimination of polarization from scattered light, we report on the effects of different anisotropic illumination models and different dust models on the summary parameters for the Spider IFN. The summary parameters are also sensitive to the IFN location, as we illustrate using FRaNKIE illumination models. For assessing the viability of dust and aISRF models, we find that observations of ψ and p of scattered light are indeed powerful new diagnostics to complement joint modeling of the intensity of scattered light (related to the average phase function) and the intensity of thermal dust emission. However, optically thin IFNs that can be modeled using single scattering are faint and p is not large, as it could be with Rayleigh scattering, and so these observations need to be carried out with care and precision. Results for the Draco nebula compared to the Spider illustrate the challenge.

Curved OLED-based NLOS optical camera communications links.

In this paper, for the first time, to the best of our knowledge, we experimentally demonstrate the use of a curved organic light emitting diode (OLED) as a transmitter (Tx) in the non-line-of-sight (NLOS) optical camera communication (OCC) link for an indoor environment using a camera as a receiver. The proposed NLOS-OCC scheme is evaluated for the signal-to-noise ratio (SNR) and the reception success rates R r s under key photographic and communication parameters, including exposure times t e x p and gain values G v, as well as the transmission frequency f s and the distance L. The SNR analysis is performed using a binary classification procedure based on a Gaussian mixture model for the first time, to the best of our knowledge, for OLED-based NLOS-OCC links. We also derive and demonstrate that the effect of G v on the SNR with respect to L is minimal based on the pixel illumination model. The initial analysis suggests that, for a wall reflector-based NLOS-OCC link that is 2m long, the SNR and R r s increase by 1dB and 4% (83-87%) for f s of 600Hz, with an increase in t e x p of 1000-1500µs and G v of 25-45dB.

Model and Approach in Evaluation of English Language Learning

This study aims to describe theoretically the learning evaluation model and approach. The method used in this study is the literature review method. This method emphasizes textbooks as sources and studies. The results of this study found that the learning evaluation model is divided into two namely: a quantitative evaluation model and a qualitative evaluation model. Quantitative evaluation models include the black box Tyler model, theoretical model, CIPP model, and Alkin model. In contrast, the qualitative evaluation model includes a case study model, an illuminative model, and a responsive model. Learning evaluation approaches include traditional approaches and systems approaches. By applying this evaluation model and approach to learning, the learning evaluation process in the classroom will be systematic and the resulting output will be in line with the expectations of the education system

Determining the efficiency of installing fixed solar photovoltaic modules and modules with different tracking options

The object of this study is photovoltaic modules in various installation options. The physical model of the Earth's illumination by a parallel flow of solar rays has been refined. The dependence of the cosine of the angle of incidence of the Sun's rays on the angular length of the day, as well as the average annual efficiency of the installation of photovoltaic modules, both fixed and with various tracking options, was determined. Refinement of the physical model implies determining the angle of inclination as the angle between the inclined axis of the Earth and its projection on a vertical plane, perpendicular to the line connecting the centers of the Earth and the Sun. This line passes through the center of the Earth. The concept of the average annual efficiency of the installation of photovoltaic modules is introduced as the annual weighted average value of the cosine of the angle of incidence of solar rays on the plane of the photovoltaic module. Various options for installing photovoltaic modules were analyzed: fixed horizontal on the equator; stationary, installed at an angle to the horizon; one that performs tracking in horizontal (vertical) planes; with full tracking. The efficiency of installing a photovoltaic module at each latitude can be equal to the efficiency of installing this module at the equator, that is, 47.93 % when installing the module at an angle of inclination to the horizon equal to the latitude. Tracking in the vertical plane makes it possible to increase the efficiency of the photovoltaic module installation by up to 50 %. Compared to full tracking, tracking in the horizontal plane at an angle of latitude makes it possible to obtain the efficiency of the installation of the photovoltaic module at the level of 97.93 %. The results could be used as a basis for evaluating the efficiency of the installation of photovoltaic modules at different latitudes with different techniques of their installation, as well as for the subsequent generation of electricity

Evaluation of learning English with the illuminative model in the Fun English program

Evaluation of learning English with the illuminative model in the Fun English program

Digital Archiving of the Spatial Experience of Cultural Heritage Sites with Ancient Lighting

Although adaptive reuse has made the preservation, restoration, and maintenance of architectural heritage sites possible due to the revenue generated by the new program, it has unfortunately induced unavoidable renovations that have altered the original design. Consequently, while the physical configuration of an architectural scene of a heritage site can be preserved and restored to mimic how it looked in the past, how to experience it as rendered with the original lighting design that might no longer be available. With the advancement of technologies related to High Dynamic Range Imaging, light models of various ancient illumination can be reconstructed and used as lighting sources for the virtual environment. Although ancient light sources can now be preserved in this digital form, this technique falls short of preserving the real visual perception of the significant canonical scene of cultural heritage with the originally intended lighting. This study proposes a conceptual framework for the digital archiving of the perceptual realism of the original lighting scheme of an architectural heritage site. The Taiwanese folk religion temples were included in a case study to demonstrate the framework; the study investigated how to identify the discrepancy between the scene-based lighting from the past and that of the current period due to adaptive reuse; further, this study determined the systematic method to select the canonical view that can best invoke the memorial spatial experience of the historical space; additionally, this study provides a case report of the restoration of past lighting with candles made with ancient recipes that were recovered from the field study, and the computational process of documenting scene-based lighting with related technologies using high dynamic range imaging. Finally, the researcher of this study conducted two perceptual experiments. The results of the first experiment demonstrated that the pattern of light and dark induced by the daylight falling into the courtyard plays a significant role regarding the viewers’ preference of the canonical scene of the traditional temple. The second experiment further demonstrated canonical views of three temples illuminated with artificial light, modern candlelight, and ancient candlelight, with ancient lighting being the preferred option of viewers.

Algorithm for Automatic Generation of Oil Painting Guidance in Colleges and Art Culture Video Based on Intelligent Brush

This paper proposes a computer-generated algorithm for college oil painting style guidance and art culture video automatic generation with intelligent brushes. This paper proposes to use the tensor eigenvector value of the smart brush as the brush direction to draw multiple layers of input video frames to effectively simulate the fluid feel of Van Gogh's oil paintings. At the same time, an improved local illumination model is proposed. mapping technology to enhance the paint layering of drawn video frames. Firstly, the multispectral PCA spectral reconstruction algorithm is used to reconstruct the spectral reflectance of the oil painting surface, and then the image information and color information of the oil painting are reproduced; secondly, the combination of physical BRDF and multispectral images is used to reproduce the spatial information and color information of oil painting samples.

Daylighting Design Methods: History and Modernity

The article is devoted to the emergence and development of methods for calculating of daylighting. The emergence of mathematical, graphical, and instrumental methods of dimension and calculation of daylighting is shown in chronological order. The authors of these methods are named. Attention is paid to modern computer methods of calculation as well as of students’ light and engineering teaching process at different time intervals. The path that science has gone from choosing the size of light apertures in buildings by empirical methods and misunderstanding the need for accurate calculations of daylighting for people’s life and performing various functions to computer illumination modelling, the obligation to teach calculation methods to students of architectural and construction specialties is shown. The review covers the period from the end of the XIX century to the present day.

Analysis of the Influence of Thermal Loading on the Behaviour of the Earth’s Crust

The article focuses on the deformation and strain-stress analysis of the Earth’s crust under external thermal loading. More specifically, the influence of cyclic changes in the surface temperature field on the stress and displacement inside the crust over a two-year time span is investigated. The finite element program MSC.Marc Mentat was used to calculate the stresses and displacements. For practical analysis reasons, the Earth’s crust is simplified as a planar, piecewise homogeneous, isotropic model (plane strain), and time-varying temperature functions of illumination (thermal radiation) from the Sun are considered in the local isotropy sections of the model. Interaction between the Earth’s crust and mantle is defined by the Winkler elastic foundation. By applying a probabilistic approach (Monte Carlo Method), a new stochastic model of displacements and stresses and new information on crustal displacements relative to the Earth’s mantle were obtained. The results proved the heating influence of the Sun on the Earth’s crust and plate tectonics.

Illumination modelling for reconstructing the machined surface topography

Illumination estimation is crucial for surface detection methods based on visual image reconstruction. The luminance of the machined surface topography with desertification fractal structure is difficult to accurately describe using existing illumination models, which depend on the macrosurface geometric features and reflection characteristics. Therefore, machined surface topography illumination model under coaxial light microscopic vision is proposed in this paper for the online detection of complex surfaces and special functional surface topography in the manufacturing field. Based on light scattering theory, the luminance of the surface topography is studied under the coaxial light microscopic vision; the influencing factors of luminance of surface topography are revealed and the illumination model of machined surface topography is established. The experimental results show that less calculation error occurs when using the proposed illumination model, which can be used to more accurately describe the luminance of machined surface topography. The research results will lay a foundation for online detection and monitoring of machined surfaces.

Biologically meaningful moonlight measures and their application in ecological research

Light availability is one of the key drivers of animal activity, and moonlight is the brightest source of natural light at night. Moon phase is commonly used but, while convenient, it can be a poor proxy for lunar illumination on the ground. While the moon phase remains effectively constant within a night, actual moonlight intensity is affected by multiple factors such as disc brightness, position of the moon, distance to the moon, angle of incidence, and cloud cover. A moonlight illumination model is presented for any given time and location, which is significantly better at predicting lunar illumination than moon phase. The model explains up to 92.2% of the variation in illumination levels with a residual standard error of 1.4%, compared to 60% explained by moon phase with a residual standard error of 22.6%. Importantly, the model not only predicts changes in mean illumination between nights but also within each night, providing greater temporal resolution of illumination estimates. An R package moonlit facilitating moonlight illumination modelling is also presented. Using a case study, it is shown that modelled moonlight intensity can be a better predictor of animal activity than moon phase. More importantly, complex patterns of activity are shown where animals focus their activity around certain illumination levels. This relationship could not be identified using moon phase alone. The model can be universally applied to a wide range of ecological and behavioural research, including existing datasets, allowing a better understanding of lunar illumination as an ecological resource.Significance statementMoon phase is often used to represent lunar illumination as an environmental niche, but it is a poor proxy for actual moonlight intensity on the ground. A model is therefore proposed to estimate lunar illumination for any given place and time. The model is shown to provide a significantly better prediction of empirically measured lunar illumination than moon phase. Importantly, it also has much higher temporal resolutions, allowing to not only detect selectiveness for light levels between nights but also within each night, which is not achievable with moon phase alone. This offers unprecedented opportunities to study complex activity patterns of nocturnal species using any time-stamped data (GPS trackers, camera traps, song meters, etc.). It can also be applied to historical datasets, as well as facilitate future research planning in a wide range of ecological and behavioural studies.

Phase Deflectometry for Defect Detection of High Reflection Objects.

A method for detecting the surface defects of high reflection objects using phase deflection is proposed. The abrupt change in the surface gradient at the defect leads to the change in the fringe phase. Therefore, Gray code combined with a four-step phase-shift method was employed to obtain the surface gradients to characterize the defects. Then, through the double surface illumination model, the relationship between illumination intensity and phase was established. The causes of periodic error interference were analyzed, and the method of adjusting the fringe width to eliminate it was proposed. Finally, experimental results showed the effectiveness of the proposed method.

High-speed rendering pipeline for polygon-based holograms

As an important three-dimensional (3D) display technology, computer-generated holograms (CGHs) have been facing challenges of computational efficiency and realism. The polygon-based method, as the mainstream CGH algorithm, has been widely studied and improved over the past 20 years. However, few comprehensive and high-speed methods have been proposed. In this study, we propose an analytical spectrum method based on the principle of spectral energy concentration, which can achieve a speedup of nearly 30 times and generate high-resolution (8K) holograms with low memory requirements. Based on the Phong illumination model and the sub-triangles method, we propose a shading rendering algorithm to achieve a very smooth and realistic reconstruction with only a small increase in computational effort. Benefiting from the idea of triangular subdivision and octree structures, the proposed original occlusion culling scheme can closely crop the overlapping areas with almost no additional overhead, thus rendering a 3D parallax sense. With this, we built a comprehensive high-speed rendering pipeline of polygon-based holograms capable of computing any complex 3D object. Numerical and optical reconstructions confirmed the generalizability of the pipeline.

EVALUATION PROGRAM APPROACH IN EDUCATION

This paper describes the evaluation program approach in education. This approach is carried out to evaluate the student’s achievement level in learning. This activity needs to be conducted to help teachers thoroughly so that inputs and processes in learning can be contained in the learning process. The use of method is applied based on a literature review through meta-analysis derived from the results of reviewing journals regarding the implementation of the evaluation program approach in learning that has the same topic in this paper, analyzed, and compared to the review results, which are described in good language. The research result indicates eight approach models in the evaluation of educational programs, which are the CIPP model, Provus model, Stake model, Kirkpatrick model, Brinkerhoff model, Congruence model, Illuminative model, and Logical model. The CIPP model is an approach that teachers often use because it includes context, input, process, and outcome evaluation. The results of applying this approach model can be carried out thoroughly so that it can be applied to every learning subject.

Optical Flow Computation for Video Under the Dynamic Illumination

Optical flow computation for video under the dynamic illumination is a challenging issue in video multimedia applications. In this paper, we solve this issue by introducing an illumination-invariant framework for variational optical flow estimation. It consists of an illumination-invariance model that handles complex illumination changes and a data enhancement model that guarantees highly accurate optical flow estimation. In this framework, we design a log-correlation descriptor for the data term, which handles complex illumination changes by eliminating the common parameters shared by the neighboring pixels in the corresponding illumination model while improving the accuracy of optical flow estimation by enhancing the discriminability of the data term matching. We also introduce a novel optical flow model with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{0}$</tex-math></inline-formula> regularizer, which reconstructs optical flow field by a sparse flow gradient counting scheme. Different from other edge-preserving regularizers, it does not depend on local motion features, but locates important flow edges globally. Therefore, it will not cause edge blurriness due to avoiding local filtering or average operation. It is particularly effective for enhancing major flow edges while eliminating a manageable degree of low-amplitude motion structures to control smoothing and reduce oversegmentation artifacts. Even small-scale motion structures with high contrast can be preserved remarkably well. The experimental results show our method significantly outperforms previous illumination-robust optical flow methods in handling complex illumination changes, and achieves competitive evaluation results on the challenging MPI-Sintel and Kitti datasets.

Error Model and Two-Phase Correction Method for Indirect Illumination

Phase shifting profilometry (PSP) has the advantages of high accuracy, spatial resolution, and anti-noise ability. However, in addition to random noise, indirect illumination, such as subsurface scattering, inter-reflection, and volume scattering, often occurs in the actual measurement environment, seriously affecting the system accuracy. In this paper, a sine series model (SSM) is proposed to simulate the error, which significantly simplifies the computational work. Based on the sine series model, a two-phase correction method (TPC) is proposed, where two phases with different frequencies are adopted to suppress the interference caused by indirect illumination and random noise. Moreover, by combining the multi-wavelength method to unwrap phase, TPC does not need to project additional patterns. Contrast experiments demonstrate that the proposed TPC method has the performance of reducing the error by 40.8%.

Automatic Shadow Generation via Exposure Fusion

Shadow generation aims to generate a plausible shadow for the inserted foreground object in a composite image. Besides the composite image and the associated mask of the inserted foreground object, existing methods also require a mask of all background objects as well as their shadows as an auxiliary input, which is laborious in practical applications. Meanwhile, most existing methods use a linear illumination transformation to darken the shadow region, which is prone to produce unrealistic shadows especially when background illumination is complex. To address these problems, this paper proposes an automatic shadow generation method, which avoids the laborious acquisition of the background object masks while harmonizing the shadow region to achieve plausible shadow effects. Specifically, to implicitly exploit background illumination to infer the shadow shape of the inserted foreground object, we first propose a Hierarchy Attention U-Net (HAU-Net) to sequentially build global interactions between the foreground object and background across spatial and channel dimensions. Since the spatial-variant property of the shadow, we formulate shadow harmonization as an exposure fusion problem and propose an Illumination-Aware Fusion Network (IFNet), which uses an improved illumination model with a double linear transformation to produce multiple under-exposure images of the shadow region. IFNet then learns pixel-wise fusion kernels that consider the local smoothness of the shadow to fuse the composite image with these under-exposure images to generate the realistic shadow of the foreground object. Extensive experiments on the DESOBA and Shadow-AR datasets demonstrate that our method achieves state-of-the-art performance for shadow generation on both the BOS and BOS-free test images.

Design of intelligent system for indoor illumination adjustment based on deep learning

In order to overcome the low adjustment accuracy and efficiency of the traditional regulation system, this paper designed an indoor lighting intensity intelligent regulation system based on deep learning. The hardware part of the system is designed by deep learning. Then, based on the analysis of sensor data and historical data, the corresponding intelligent adjustment table is formed. After the convolution and pooling operation, the training samples are combined with restricted Boltzmann machine. At the same time, the natural illumination model is built based on the time cycle variation characteristics of sunlight, and the indoor and outdoor illumination is calculated with the deep learning results, so as to obtain the brightness level of dimming and to realise intelligent regulation. The experimental results show that the intelligent adjustment accuracy of the system is between 95.0% and 98.5%, and the adjustment efficiency is always above 95%.

Multispectral imaging of nailfold capillaries using light-emitting diode illumination.

The capillaries are the smallest blood vessels in the body, typically imaged using video capillaroscopy to aid diagnosis of connective tissue diseases, such as systemic sclerosis. Video capillaroscopy allows visualization of morphological changes in the nailfold capillaries but does not provide any physiological information about the blood contained within the capillary network. Extracting parameters such as hemoglobin oxygenation could increase sensitivity for diagnosis and measurement of microvascular disease progression. To design, construct, and test a low-cost multispectral imaging (MSI) system using light-emitting diode (LED) illumination to assess relative hemoglobin oxygenation in the nailfold capillaries. An LED ring light was first designed and modeled. The ring light was fabricated using four commercially available LED colors and a custom-designed printed circuit board. The experimental system was characterized and results compared with the illumination model. A blood phantom with variable oxygenation was used to determine the feasibility of using the illumination-based MSI system for oximetry. Nailfold capillaries were then imaged in a healthy subject. The illumination modeling results were in close agreement with the constructed system. Imaging of the blood phantom demonstrated sensitivity to changing hemoglobin oxygenation, which was in line with the spectral modeling of reflection. The morphological properties of the volunteer capillaries were comparable to those measured in current gold standard systems. LED-based illumination could be used as a low-cost approach to enable MSI of the nailfold capillaries to provide insight into the oxygenation of the blood contained within the capillary network.