scholarly journals Learning Effective Skeletal Representations on RGB Video for Fine-Grained Human Action Quality Assessment

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 568 ◽  
Author(s):  
Qing Lei ◽  
Hong-Bo Zhang ◽  
Ji-Xiang Du ◽  
Tsung-Chih Hsiao ◽  
Chih-Cheng Chen
Keyword(s):  
Regression Model ◽  
Quality Assessment ◽  
Human Action ◽  
Feature Descriptor ◽  
Camera Motion ◽  
Self Similarity ◽  
Fine Grained ◽  
Testing Stage ◽  
The Impact

In this paper, we propose an integrated action classification and regression learning framework for the fine-grained human action quality assessment of RGB videos. On the basis of 2D skeleton data obtained per frame of RGB video sequences, we present an effective representation of joint trajectories to train action classifiers and a class-specific regression model for a fine-grained assessment of the quality of human actions. To manage the challenge of view changes due to camera motion, we develop a self-similarity feature descriptor extracted from joint trajectories and a joint displacement sequence to represent dynamic patterns of the movement and posture of the human body. To weigh the impact of joints for different action categories, a class-specific regression model is developed to obtain effective fine-grained assessment functions. In the testing stage, with the supervision of the action classifier’s output, the regression model of a specific action category is selected to assess the quality of skeleton motion extracted from the action video. We take advantage of the discrimination of the action classifier and the viewpoint invariance of the self-similarity feature to boost the performance of the learning-based quality assessment method in a realistic scene. We evaluate our proposed method using diving and figure skating videos of the publicly available MIT Olympic Scoring dataset, and gymnastic vaulting videos of the recent benchmark University of Nevada Las Vegas (UNLV) Olympic Scoring dataset. The experimental results show that the proposed method achieved an improved performance, which is measured by the mean rank correlation coefficient between the predicted regression scores and the ground truths.

scholarly journals The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context

2015 ◽  
Vol 15 (7) ◽  
pp. 88-98
Author(s):  
J. Dezert ◽  
A. Tchamova ◽  
P. Konstantinova
Keyword(s):  
Quality Assessment ◽  
Data Association ◽  
New Method ◽  
Multitarget Tracking ◽  
Belief Functions ◽  
Tracking Systems ◽  
Optimal Assignment ◽  
The Individual ◽  
The Impact

Abstract The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association solution for improving the performances of multisensor-multitarget tracking systems. The advantages of its implementation in an illustrative realistic surveillance context, when some of the association decisions are unreliable and doubtful and lead to potentially critical mistake, are discussed. A comparison with the results obtained on the base of Generalized Data Association is made.

scholarly journals The Influence of the Use of Polymer Lining within the Roller Press Gravity Feeder on Briquette Quality

Polymers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2489
Author(s):  
Michał Bembenek
Keyword(s):  
Molecular Weight ◽  
High Molecular Weight ◽  
Material Flow ◽  
Laboratory Tests ◽  
Polymer Materials ◽  
Roller Press ◽  
Fine Grained ◽  
The Impact ◽  
Ultra High Molecular Weight

When considering the operation of roller presses for the consolidation of fine-grained materials, the main problems are disturbances in the proper flow of the material and its bridging in gravity feeders. This is especially true for small and medium capacity presses, where the hoppers for dosing the material are narrow. This article presents innovative laboratory tests of the impact of using a polymer plate lining in the gravity feeder of a roller press. Polymer materials Polyacetal C (POM C) and Ultra-High-Molecular-Weight Polyethylene (UHMW-PE) were used for the tests. The influence of the use of plates on the material flow and quality of briquettes was investigated in comparison with the case where such plates were not used. The research showed an improvement in the flow of fine-grained materials in the feeder and an increase of the briquette strength indexes, as compared to those cases when polymer linings were not used in the feeder.

Feature Extraction and Representation for Distributed Multi-View Human Action Recognition

2013 ◽  
Vol 3 (2) ◽  
pp. 145-154 ◽  
Author(s):  
Jiajia Luo ◽  
Wei Wang ◽  
Hairong Qi
Keyword(s):  
Action Recognition ◽  
Approximation Error ◽  
Human Action Recognition ◽  
Human Action ◽  
Base Station ◽  
Feature Representation ◽  
Superior Performance ◽  
Feature Descriptor ◽  
Testing Stage ◽  
New Feature

Multi-view human action recognition has gained a lot of attention in recent years for its superior performance as compared to single view recognition. In this paper, we propose a new framework for the real-time realization of human action recognition in distributed camera networks (DCNs). We first present a new feature descriptor (Mltp-hist) that is tolerant to illumination change, robust in homogeneous region and computationally efficient. Taking advantage of the proposed Mltp-hist, the noninformative 3-D patches generated from the background can be further removed automatically that effectively highlights the foreground patches. Next, a new feature representation method based on sparse coding is presented to generate the histogram representation of local videos to be transmitted to the base station for classification. Due to the sparse representation of extracted features, the approximation error is reduced. Finally, at the base station, a probability model is produced to fuse the information from various views and a class label is assigned accordingly. Compared to the existing algorithms, the proposed framework has three advantages while having less requirements on memory and bandwidth consumption: 1) no preprocessing is required; 2) communication among cameras is unnecessary; and 3) positions and orientations of cameras do not need to be fixed. We further evaluate the proposed framework on the most popular multi-view action dataset IXMAS. Experimental results indicate that our proposed framework repeatedly achieves state-of-the-art results when various numbers of views are tested. In addition, our approach is tolerant to the various combination of views and benefit from introducing more views at the testing stage. Especially, our results are still satisfactory even when large misalignment exists between the training and testing samples.

scholarly journals The role of safety in service quality in the opinion of traditional and digital customers of postal service

2020 ◽  
Vol 26 (1) ◽  
pp. 1-4
Author(s):  
Kamila Kowalik
Keyword(s):  
Service Quality ◽  
Quality Assessment ◽  
Theoretical Framework ◽  
Postal Service ◽  
Perception Of Safety ◽  
Postal Services ◽  
Safety Attributes ◽  
The Impact

AbstractOne of the factors allowing to shape safety and quality of a postal service is an opinion of its customer. In the following paper, the analysis of the impact of a customer’s perception of safety on the service quality assessment has been presented. Research results presented in the paper refer to opinions of traditional and digital customers of postal services. The presented analysis is enriched by a theoretical framework of service quality, the explanation of the concept of safety, and a complementary characteristics of traditional and digital postal services. Afterwards, safety attributes of the postal services have been proposed, explained and highlighted. Subsequently, the results presented in the paper refer to the validity of particular chosen safety attributes of postal services.

scholarly journals NO-REFERENCE IMAGE QUALITY ASSESSMENT FOR ZY3 IMAGERY IN URBAN AREAS USING STATISTICAL MODEL

2016 ◽  
Vol XLI-B3 ◽  
pp. 949-954 ◽  
Author(s):  
Y. Zhang ◽  
W.H. Cui ◽  
F. Yang ◽  
Z.C. Wu
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Urban Areas ◽  
Satellite Images ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Atmospheric Conditions ◽  
Natural Scene Statistics ◽  
The Impact

More and more high-spatial resolution satellite images are produced with the improvement of satellite technology. However, the quality of images is not always satisfactory for application. Due to the impact of complicated atmospheric conditions and complex radiation transmission process in imaging process the images often suffer deterioration. In order to assess the quality of remote sensing images over urban areas, we proposed a general purpose image quality assessment methods based on feature extraction and machine learning. We use two types of features in multi scales. One is from the shape of histogram the other is from the natural scene statistics based on Generalized Gaussian distribution (GGD). A 20-D feature vector for each scale is extracted and is assumed to capture the RS image quality degradation characteristics. We use SVM to learn to predict image quality scores from these features. In order to do the evaluation, we construct a median scale dataset for training and testing with subjects taking part in to give the human opinions of degraded images. We use ZY3 satellite images over Wuhan area (a city in China) to conduct experiments. Experimental results show the correlation of the predicted scores and the subjective perceptions.

scholarly journals The Impact of Compliance with Codes of Corporate Governance on Quality of Disclosure: Comparative Study between Palestine and Jordan

2016 ◽  
Vol 8 (9) ◽  
pp. 215
Author(s):  
Naser - Abdelkarim ◽  
Mohammed T. Abusharbeh
Keyword(s):  
Corporate Governance ◽  
Regression Model ◽  
Listed Companies ◽  
Multiple Regression Model ◽  
Financial Data ◽  
Listed Firms ◽  
Governance Practices ◽  
The Impact ◽  
Analyze Data

<p>This study seeks to achieve two objectives; (1) to examine the degree of compliance with corporate governance requirements in Palestine and Jordan by listed firms, and (2) to investigate the impact of corporate governance on quality of disclosure for Palestinian and Jordanian listed firms. A sample of 15 Palestinian listed companies and 30 Jordanian listed companies that fully disclosed their financial data in year 2007 and 2014 was used. This research employs multiple regression model and one sample t-test in order to analyze data variables and to test the research hypotheses.The research reveals that there are no statistically significant differences between Jordan and Palestinian listed firms in applying the respective codes of corporate governance, but these two countries are relatively still modest in observing corporate governance rules. This study also concludes that boards of director’s characteristics have no significant impact on quality of disclosure in Palestine and Jordan. This indicates that corporate governance practices didn’t have any significant effect on quality of disclosurefor Palestinian and Jordanian listed firms.</p>

Accelerated Compression Algorithm Based on Factoring Repeated Content

2013 ◽  
Vol 760-762 ◽  
pp. 1972-1977
Author(s):  
Ying Tang ◽  
Xi Huan Zhu
Keyword(s):  
The Self ◽  
Feature Descriptor ◽  
Compression Method ◽  
Self Similarity ◽  
Compression Process ◽  
Computing Power ◽  
Feature Descriptors ◽  
Order Of Magnitude ◽  
Similarity Computation

In this paper, we introduce the accelerated image compression method to reduce memory and bandwidth cost by factoring repeated content within images. Since the compression procedure costs much time to search for the similar regions, we adopt the feature descriptor Gray Split Rotate (GSR) to accelerate the self-similarity computation. The self-similarity computation is partly transformed into the comparison of the distances between feature descriptors. And we find that the computations of GSR distances of each feature descriptors are independent with each other. By the use of GPU parallel computing power, we filter out a huge amount of unmatched candidates. In our experiments we improve the speed of the compression process by one order of magnitude and meanwhile still preserve the quality of the compressed image by reducing unnecessary candidates.

Regression-Based Automated Facial Image Quality Model

2017 ◽  
Vol 11 (4) ◽  
pp. 22-40 ◽  
Author(s):  
Fatema Tuz Zohra ◽  
Andrei D. Gavrilov ◽  
Omar A. Zatarain ◽  
Marina L. Gavrilova
Keyword(s):  
Face Recognition ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Analysis ◽  
Recognition System ◽  
Quality Factors ◽  
Quality Estimation ◽  
Face Recognition System ◽  
The Impact

Nowadays, biometric technologies became reliable and widespread means of unobtrusive user authentication in a variety of real-world applications. The performance of an automated face recognition system has a strong relationship with the quality of the biometric samples. The facial samples can be affected by various quality factors, such as uneven illumination, low or high contrast, excessive brightness, blurriness, etc. In this article, the authors propose a quality estimation method based on linear regression analysis to characterize the relationship between different quality factors and the performance of a face recognition system. The regression model can predict the overall quality of a facial sample which reflects the effects of various quality factors on that sample. The weights assigned to the different quality factors by the linear regression model reflect the impact of those quality factors on the performance of the recognition system. Therefore, the prediction scores generated from the model is a strong indicator of the overall quality of the facial images. The authors evaluated the quality estimation model on the Extended Yale Database B. They also performed a study to understand which quality factors affect the face recognition the most.

Digital Image Documentation for Quality Assessment

2001 ◽  
Vol 125 (11) ◽  
pp. 1430-1435
Author(s):  
Domingos Cruz ◽  
Carla Valentí ◽  
Aureliano Dias ◽  
Mário Seixas ◽  
Fernando Schmitt
Keyword(s):  
Quality Assessment ◽  
Digital Image ◽  
Feasible Solution ◽  
Digital Images ◽  
Region Of Interest ◽  
Routine Practice ◽  
Diagnostic Quality ◽  
Higher Power ◽  
The Impact

Abstract Objective.—To demonstrate the feasibility of the use of digital images to document routine cases and to perform diagnostic quality assessment. Methods.—Pathologists documented cases by acquiring up to 12 digital images per case. The images were sampled at 25:1, 50:1, 100:1, 200:1, or 400:1 magnifications, according to adequacy in aiding diagnosis. After each acquisition, the referral pathologist marked a region of interest within each acquired image in order to evaluate intrinsic redundancy. The extrinsic redundancy was determined by counting the unnecessary images. Cases were randomly selected and reviewed by one pathologist. The quality of each image, the possibility of accomplishing a diagnosis based on images, and the degree of agreement was evaluated. Results.—During routine practice, 1469 cases were documented using 3902 images. Most of the images were acquired at higher power magnifications. From all acquired cases, 143 cases and their 373 related images were randomly selected for review. In 88.1% (126/143) of reviewed cases, it was possible to accomplish the diagnosis based on images. In 30.2% (38/126) of these cases, the reviewer considered that the diagnosis could be accomplished with fewer images. The referral pathologist and the reviewer found intrinsic redundancy in 57.8% and 54.5% of images, respectively. Conclusions.—Our results showed that digital image documentation to perform diagnostic quality assessment is a feasible solution. However, owing to the impact on routine practice, guidelines for acquisition and documentation of cases may be needed.

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