scholarly journals Quality Assessment of 3D Synthesized Images Based on Textural and Structural Distortion Estimation

2021 ◽  
Vol 11 (6) ◽  
pp. 2666
Author(s):  
Hafiz Muhammad Usama Hassan Alvi ◽  
Muhammad Shahid Farid ◽  
Muhammad Hassan Khan ◽  
Marcin Grzegorzek
Keyword(s):  
Quality Assessment ◽  
Mixed Reality ◽  
Depth Estimation ◽  
Poor Quality ◽  
Depth Image ◽  
Depth Maps ◽  
Structural Distortions ◽  
Image Quality Metric ◽  
Technological Constraints

Emerging 3D-related technologies such as augmented reality, virtual reality, mixed reality, and stereoscopy have gained remarkable growth due to their numerous applications in the entertainment, gaming, and electromedical industries. In particular, the 3D television (3DTV) and free-viewpoint television (FTV) enhance viewers’ television experience by providing immersion. They need an infinite number of views to provide a full parallax to the viewer, which is not practical due to various financial and technological constraints. Therefore, novel 3D views are generated from a set of available views and their depth maps using depth-image-based rendering (DIBR) techniques. The quality of a DIBR-synthesized image may be compromised for several reasons, e.g., inaccurate depth estimation. Since depth is important in this application, inaccuracies in depth maps lead to different textural and structural distortions that degrade the quality of the generated image and result in a poor quality of experience (QoE). Therefore, quality assessment DIBR-generated images are essential to guarantee an appreciative QoE. This paper aims at estimating the quality of DIBR-synthesized images and proposes a novel 3D objective image quality metric. The proposed algorithm aims to measure both textural and structural distortions in the DIBR image by exploiting the contrast sensitivity and the Hausdorff distance, respectively. The two measures are combined to estimate an overall quality score. The experimental evaluations performed on the benchmark MCL-3D dataset show that the proposed metric is reliable and accurate, and performs better than existing 2D and 3D quality assessment metrics.

scholarly journals A Layered Approach for Quality Assessment of DIBR-Synthesized Images

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Rafia Mansoor ◽  
Muhammad Shahid Farid ◽  
Muhammad Hassan Khan ◽  
Asma Maqsood
Keyword(s):  
Quality Assessment ◽  
Color Image ◽  
Three Dimensional ◽  
Depth Map ◽  
Poor Quality ◽  
Depth Image ◽  
Multiview Video ◽  
3D Scene ◽  
2D And 3D

Multiview video plus depth (MVD) is a popular video format that supports three-dimensional television (3DTV) and free viewpoint television (FTV). 3DTV and FTV provide depth sensation to the viewer by presenting two views of the same scene but with slightly different angles. In MVD, few views are captured, and each view has the color image and the corresponding depth map which is used in depth image-based rendering (DIBR) to generate views at novel viewpoints. The DIBR can introduce various artifacts in the synthesized view resulting in poor quality. Therefore, evaluating the quality of the synthesized image is crucial to provide an appreciable quality of experience (QoE) to the viewer. In a 3D scene, objects are at a different distance from the camera, characterized by their depth. In this paper, we investigate the effect that objects at a different distance make on the overall QoE. In particular, we find that the quality of the closer objects contributes more to the overall quality as compared to the background objects. Based on this phenomenon, we propose a 3D quality assessment metric to evaluate the quality of the synthesized images. The proposed metric using the depth of the scene divides the image into different layers where each layer represents the objects at a different distance from the camera. The quality of each layer is individually computed, and their scores are pooled together to obtain a single quality score that represents the quality of the synthesized image. The performance of the proposed metric is evaluated on two benchmark DIBR image databases. The results show that the proposed metric is highly accurate and performs better than most existing 2D and 3D quality assessment algorithms.

scholarly journals Quality assessment of nutrition coverage in the media: a 6-week survey of five popular UK newspapers

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e014633 ◽  
Author(s):  
Alice R Kininmonth ◽  
Nafeesa Jamil ◽  
Nasser Almatrouk ◽  
Charlotte E L Evans
Keyword(s):  
Health Outcome ◽  
Quality Assessment ◽  
Assessment Tool ◽  
Poor Quality ◽  
Quality Score ◽  
Food Type ◽  
The Public ◽  
Day Of The Week ◽  
Article Quality

ObjectivesTo investigate the quality of nutrition articles in popular national daily newspapers in the UK and to identify important predictors of article quality.SettingNewspapers are a primary source of nutrition information for the public.DesignNewspaper articles were collected on 6 days of the week (excluding Sunday) for 6 weeks in summer 2014. Predictors included food type and health outcome, size of article, whether the journalist was named and day of the week.Outcome measuresA validated quality assessment tool was used to assess each article, with a minimum possible score of −12 and a maximum score of 17. Newspapers were checked in duplicate for relevant articles. The association of each predictor on article quality score was analysed adjusting for remaining predictors. A logistic regression model was implemented with quality score as the binary outcome, categorised as poor (score less than zero) or satisfactory (score of zero or more).ResultsOver 6 weeks, 141 nutrition articles were included across the five newspapers. The median quality score was 2 (IQR −2–6), and 44 (31%) articles were poor quality. There was no substantial variation in quality of reporting between newspapers once other factors such as anonymous publishing, health outcome, aspect of diet covered and day of the week were taken into account. Particularly low-quality scores were obtained for anonymously published articles with no named journalist, articles that focused on obesity and articles that reported on high fat and processed foods.ConclusionsThe general public are regularly exposed to poor quality information in newspapers about what to eat to promote health, particularly articles reporting on obesity. Journalists, researchers, university press officers and scientific journals need to work together more closely to ensure clear, consistent nutrition messages are communicated to the public in an engaging way.

scholarly journals No-Reference Depth Map Quality Evaluation Model Based on Depth Map Edge Confidence Measurement in Immersive Video Applications

2019 ◽  
Vol 11 (10) ◽  
pp. 204 ◽  
Author(s):  
Dogan ◽  
Haddad ◽  
Ekmekcioglu ◽  
Kondoz
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Depth Map ◽  
Depth Image ◽  
Depth Maps ◽  
Model Based ◽  
Objective Quality ◽  
Quality Evaluation Model ◽  
Confidence Measurement

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance.

scholarly journals A single-model quality assessment method for poor quality protein structure

2020 ◽  
Author(s):  
Jianquan Ouyang ◽  
Ningqiao Huang ◽  
Yunqi Jiang
Keyword(s):  
Protein Structure ◽  
Quality Assessment ◽  
Structure Prediction ◽  
Assessment Method ◽  
Poor Quality ◽  
Single Model ◽  
Model Quality ◽  
Model Quality Assessment ◽  
Quality Assessment Method

Abstract Quality assessment of protein tertiary structure prediction models, in which structures of the best quality are selected from decoys, is a major challenge in protein structure prediction, and is crucial to determine a model’s utility and potential applications. Estimating the quality of a single model predicts the model’s quality based on the single model itself. In general, the Pearson correlation value of the quality assessment method increases in tandem with an increase in the quality of the model pool. However, there is no consensus regarding the best method to select a few good models from the poor quality model pool. In this work, we introduce a novel single-model quality assessment method for poor quality models that uses simple linear combinations of six features. We perform weighted search and linear regression on a large dataset of models from the 12th Critical Assessment of Protein Structure Prediction (CASP12) and benchmark the results on CASP13 models. We demonstrate that our method achieves outstanding performance on poor quality models.

scholarly journals A framework for estimating relative depth in video

2021 ◽  
Author(s):  
Richard Rzeszutek
Keyword(s):  
Depth Estimation ◽  
Theoretical Background ◽  
Depth Information ◽  
Relative Depth ◽  
Depth Estimate ◽  
New Approach ◽  
Depth Maps ◽  
Computational Overhead ◽  
Two Stages

This dissertation proposes a novel framework for recovering relative depth maps from a video. The framework is composed of two parts: a depth estimator and a sparse label interpolator. These parts are completely separate from one another and can operate independently. Prior methods have tended to heavily couple the interpolation stage with the depth estimation, which can assist with automation at the expense of flexibility. The loss of this flexibility can in fact be worse than any advantage gained by coupling the two stages together. This dissertation shows how by treating the two stages separately, it is very easy to change the quality of the results with little effort. It also leaves room for other adjustments. The depth estimator is based upon well-established computer vision principles and only has the restriction that the camera must be moving in order to obtain depth estimates. By starting from first principles, this dissertation has developed a new approach for quickly estimating relative depth. That is, it is able to answer the question, “is this feature closer than another," with relatively little computational overhead. The estimator is designed using a pipeline-style approach so that it produces sparse depth estimates in an online fashion; i.e. a depth estimate is automatically available for each new frame presented to the estimator. Finally, the interpolator applies an existing method based upon edge-aware filtering to generate the final depth maps. When temporal filters are used, the interpolation stage is able to very easily handle frames without any depth information, such as when the camera was stationary. However, unlike the prior work, this dissertation establishes the theoretical background for this type of interpolation and addresses some of the associated numerical problems. Strategies for dealing with these issues have also been provided

Photoplethysmogram Signal Quality Assessment Using Support Vector Machine and Multi-Feature Fusion

2018 ◽  
Vol 8 (9) ◽  
pp. 1757-1762 ◽  
Author(s):  
Jie Zhang ◽  
Licai Yang ◽  
Zhonghua Su ◽  
Xueqin Mao ◽  
Kan Luo ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Quality Assessment ◽  
Feature Fusion ◽  
Poor Quality ◽  
Heart Beat ◽  
Support Vector ◽  
Signal Quality ◽  
Physiological Signal ◽  
Quality Signals

Background: Noise is unavoidable in the physiological signal measurement system. Poor quality signals can affect the results of analysis and disable the following clinical diagnosis. Thus, it is necessary to perform signal quality assessment before we interpreting the signal. Objective: In this work, we describe a method combing support vector machine (SVM) and multi-feature fusion for assessing the signal quality of pulsatile waveforms, concentrating on the photoplethysmogram (PPG). Methods: PPG signals from 53 healthy volunteers were recorded. Each had a 5 min length. Signal quality in each heart beat was manual annotated by clinical expert, and then the signal quality in 5 s episode was automatically calculated according to the results from each beat segments, resulting in a total of 13,294 5-s PPG segments. Then a SVM was trained to classify clean/noisy PPG recordings by inputting a set of twelve signal quality features. Further experiments were carried out to verify the proposed SVM based signal quality classifier method. Results: An average accuracy of 87.90%, a sensitivity of 88.10% and a specificity of 87.66% were found on the 10-fold cross validation. Conclusions: The signal quality of PPGs can be accurately classified by using the proposed method.

scholarly journals A framework for estimating relative depth in video

2021 ◽  
Author(s):  
Richard Rzeszutek
Keyword(s):  
Depth Estimation ◽  
Theoretical Background ◽  
Depth Information ◽  
Relative Depth ◽  
Depth Estimate ◽  
New Approach ◽  
Depth Maps ◽  
Computational Overhead ◽  
Two Stages

This dissertation proposes a novel framework for recovering relative depth maps from a video. The framework is composed of two parts: a depth estimator and a sparse label interpolator. These parts are completely separate from one another and can operate independently. Prior methods have tended to heavily couple the interpolation stage with the depth estimation, which can assist with automation at the expense of flexibility. The loss of this flexibility can in fact be worse than any advantage gained by coupling the two stages together. This dissertation shows how by treating the two stages separately, it is very easy to change the quality of the results with little effort. It also leaves room for other adjustments. The depth estimator is based upon well-established computer vision principles and only has the restriction that the camera must be moving in order to obtain depth estimates. By starting from first principles, this dissertation has developed a new approach for quickly estimating relative depth. That is, it is able to answer the question, “is this feature closer than another," with relatively little computational overhead. The estimator is designed using a pipeline-style approach so that it produces sparse depth estimates in an online fashion; i.e. a depth estimate is automatically available for each new frame presented to the estimator. Finally, the interpolator applies an existing method based upon edge-aware filtering to generate the final depth maps. When temporal filters are used, the interpolation stage is able to very easily handle frames without any depth information, such as when the camera was stationary. However, unlike the prior work, this dissertation establishes the theoretical background for this type of interpolation and addresses some of the associated numerical problems. Strategies for dealing with these issues have also been provided

scholarly journals INFLUENCE OF THE ENERGY FACTOR ON THE QUALITY OF HOUSEHOLD LIFE

2017 ◽  
Vol 2017 (4) ◽  
pp. 18-22
Author(s):  
Ирина Белик ◽  
Irina Belik ◽  
Людмила Камдина ◽  
Lyudmila Camdina
Keyword(s):  
Climate Change ◽  
Quality Of Life ◽  
Quality Assessment ◽  
Life Quality ◽  
Poor Quality ◽  
Resource Consumption ◽  
Energy Approach ◽  
Consumer Spending ◽  
Energy Factor

The article provides a justification for taking into account the energy factor in assessing the quality of life of households. The result of the study is the conclusion that the provision of social and economic development, which can be estimated by using such a composite indicator as the quality of life of the population (households), should include such parameters as reducing the level of resource consumption and reducing the anthropogenic load on the natural environment. To assess the quality of life of the population (households), it is important to take into account such energy factor as the level of energy saving, which affects environmental and climate change. Increased energy consumption contributes to the pollution of atmospheric air with CO2 and, as a result, to climate change and the occurrence of natural anomalies and environmental disasters. The research involves an analysis of the dynamics of incomes and consumer spending of households (including expenditures on housing and utility services). The analysis allows the authors to conclude that the quality of life of households is reduced due to the outstripping growth of consumer spending over their incomes, which can be explained by a decrease in the efficiency of energy supply. Another reason is an increase in the energy intensity of the housing and communal services due to energy loss caused by poor quality of living quarters. Given the role of the energy factor in assessing the quality of life, the authors use the ecological and energy approach to expand the current methods by including indicators that would assess its impact. The result of the study is an improved methodology for life quality assessment in terms of the energy factor. The article provides an accurate description of the indicators and the calculating procedure. In the opinion of the authors, the use of the ecological and energy approach to life quality assessment and its application for territorial comparisons (countries, regions, cities) will help to justify the mismatch between the growth rates of people’s wellbeing and the resource consumption (energy, biological, etc.).

scholarly journals A single-model quality assessment method for poor quality protein structure

2020 ◽  
Author(s):  
Jianquan Ouyang ◽  
Ningqiao Huang ◽  
Yunqi Jiang
Keyword(s):  
Protein Structure ◽  
Quality Assessment ◽  
Structure Prediction ◽  
Assessment Method ◽  
Poor Quality ◽  
Single Model ◽  
Model Quality ◽  
Model Quality Assessment ◽  
Quality Assessment Method

Abstract Background: Quality assessment of protein tertiary structure prediction models, in which structures of the best quality are selected from decoys, is a major challenge in protein structure prediction, and is crucial to determine a model’s utility and potential applications. Estimating the quality of a single model predicts the model’s quality based on the single model itself. In general, the Pearson correlation value of the quality assessment method increases in tandem with an increase in the quality of the model pool. However, there is no consensus regarding the best method to select a few good models from the poor quality model pool.Results: We introduce a novel single-model quality assessment method for poor quality models that uses simple linear combinations of six features. We perform weighted search and linear regression on a large dataset of models from the 12th Critical Assessment of Protein Structure Prediction (CASP12) and benchmark the results on CASP13 models. We demonstrate that our method achieves outstanding performance on poor quality models.Conclusions: According to results of poor protein structure assessment based on six features, contact prediction and relying on fewer prediction features can improve selection accuracy.

scholarly journals Depth Map Renement Using Reliability Based Joint Trilateral Filter

1970 ◽  
Vol 7 (2) ◽  
pp. 107-116
Author(s):  
Takuya Matsuo ◽  
Naoki Kodera ◽  
Norishige Fukushima ◽  
Yutaka Ishibashi
Keyword(s):  
Lower Cost ◽  
Computational Cost ◽  
Depth Map ◽  
Optimization Methods ◽  
Depth Image ◽  
Depth Maps ◽  
Trilateral Filter ◽  
Depth Image Based Rendering ◽  
Depth Ranges

In this paper, we propose a renement lter for depth maps. The lter convolutes an image and a depth map with a cross computed kernel. We call the lter joint trilateral lter. Main advantages of the proposed method are that the lter ts outlines of objects in the depth map to silhouettes in the im- age, and the lter reduces Gaussian noise in other areas. The eects reduce rendering artifacts when a free viewpoint image is generated by point cloud ren- dering and depth image based rendering techniques. Additionally, their computational cost is independent of depth ranges. Thus we can obtain accurate depth maps with the lower cost than the conventional ap- proaches, which require Markov random eld based optimization methods. Experimental results show that the accuracy of the depth map in edge areas goes up and its running time decreases. In addition, the lter improves the accuracy of edges in the depth map from Kinect sensor. As results, the quality of the rendering image is improved.

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