Content Screening Research Articles

Subjective and Objective Quality Assessment of Compressed Screen Content Videos

With the widespread of application scenarios such as remote office and cloud collaboration, Screen Content Video (SCV) and its processing which show different characteristics from Natural Scene Video (NSV) and its processing, are increasingly attracting researcher's attention. Among these processing techniques, quality evaluation plays an important role in various media processing systems. Despite extensive research on general Image Quality Assessment (IQA) and Video Quality Assessment (VQA), quality assessment of SCVs remains undeveloped. In particular, SCVs always suffer from compression degradations in all kinds of application scenarios. In this article, we first study subjective SCV quality assessment. Specifically, we first construct a Compressed Screen Content Video Quality (CSCVQ) database with 165 distorted SCVs compressed from 11 most common screen application scenarios using the H.264, HEVC and HEVC-SCC formats. Twenty subjects were recruited to participate in the subjective test on the CSCVQ database. Then we study objective SCV quality assessment and propose a SCV quality measure. We observe that localized protruding information such as curves and dots can be well captured by the local relative standard deviation which then can be used to measure the intra-frame quality. Base on this observation, we develop a MutiScale Relative Standard Deviation Similarity (MS-RSDS) model for SCV quality evaluation. In our model, the relative standard deviation similarity between the reference and distorted SCVs is measured from frame differences between two adjacent frames, which can capture the spatiotemporal distortions accurately. A multiscale strategy is also applied to strengthen the original single-scale model. Extensive experiments are performed to compare the proposed model with the most popular and state-of-the-art quality assessment models on the CSCVQ database. Experimental results show that our proposed MS-RSDS model which has relatively low computation complexity, outperforms other IQA/VQA models.

Hybrid neuromuscular training promotes musculoskeletal adaptations in inactive overweight and obese women: A training-detraining randomized controlled trial

ABSTRACT This study investigated the effects of a 10-month high-intensity interval-type neuromuscular training programme on musculoskeletal fitness in overweight and obese women. Forty-nine inactive females (36.4 ± 4.4 yrs) were randomly assigned to either a control (N = 21), a training (N = 14, 10 months) or a training-detraining group (N = 14, 5 months training followed by 5 months detraining). Training used progressive loaded fundamental movement patterns with prescribed work-to-rest intervals (1:2, 1:1, 2:1) in a circuit fashion (2–3 rounds). Muscular strength and endurance, flexibility, passive range of motion (PRoM), static balance, functional movement screen (FMS) and bone mass density (BMD) and content (BMC) were measured at pre-, mid-, and post-intervention. Ten months of training induced greater changes than the controls in (i) BMD (+1.9%, p < 0.001) and BMC (+1.5%, p = 0.023) ii) muscular strength (25%-53%, p = 0.001–0.005); iii) muscular endurance (103%-195%, p < 0.001); and iv) mobility (flexibility: 40%, p < 0.001; PRoM [24%-53%, p = 0.001–0.05;]; balance: 175%, p = 0.058; FMS: +58%, p < 0.001). The response rate to training was exceptionally high (86–100%). Five months of detraining reduced but not abolished training-induced adaptations. These results suggest that a hybrid-type exercise approach integrating endurance-based bodyweight drills with resistance-based alternative modes into a real-world gym setting may promote musculoskeletal fitness in overweight and obese women.

No Reference Quality Assessment for Screen Content Images Using Stacked Autoencoders in Pictorial and Textual Regions.

Recently, the visual quality evaluation of screen content images (SCIs) has become an important and timely emerging research theme. This article presents an effective and novel blind quality evaluation metric for SCIs by using stacked autoencoders (SAE) based on pictorial and textual regions. Since the SCI consists of not only the pictorial area but also the textual area, the human visual system (HVS) is not equally sensitive to their different distortion types. First, the textual and pictorial regions can be obtained by dividing an input SCI via an SCI segmentation metric. Next, we extract quality-aware features from the textual region and pictorial region, respectively. Then, two different SAEs are trained via an unsupervised approach for quality-aware features that are extracted from these two regions. After the training procedure of the SAEs, the quality-aware features can evolve into more discriminative and meaningful features. Subsequently, the evolved features and their corresponding subjective scores are input into two regressors for training. Each regressor can obtain one output predictive score. Finally, the final perceptual quality score of a test SCI is computed by these two predicted scores via a weighted model. Experimental results on two public SCI-oriented databases have revealed that the proposed scheme can compare favorably with the existing blind image quality assessment metrics.

Blind Quality Evaluation for Screen Content Images Based on Regionalized Structural Features

Currently, screen content images (SCIs) are widely used in our modern society. However, since SCIs have distinctly different properties compared to natural images, traditional quality assessment methods of natural images cannot precisely evaluate the quality of SCIs. Thus, we propose a blind quality evaluation method for SCIs based on regionalized structural features that are closely relevant to the intrinsic quality of SCIs. Firstly, the features of textual and pictorial regions of SCIs are extracted separately. For textual regions, since they contain noticeable structural information, we propose improved histograms of oriented gradients extracted from multi-order derivatives as structural features. For pictorial regions, since human vision is sensitive to texture information and luminance variation, we adopt texture as the structural feature; meanwhile, luminance is used as the auxiliary feature. The local derivative pattern and the shearlet local binary pattern are used to extract texture in the spatial and shearlet domains, respectively. Secondly, to derive the quality of textual and pictorial regions, two mapping functions are respectively trained from their features to subjective values. Finally, an activity weighting strategy is proposed to combine the quality of textual and pictorial regions. Experimental results show that the proposed method achieves better performance than the state-of-the-art methods.

An Ultralow Complexity String Matching Approach to Screen Content Coding in AVS3

Screen content coding (SCC) is increasingly used in mobile devices, and ultralow coding complexity is required for low power consumption. This article proposes an ultralow complexity string matching approach to SCC. The proposed approach has two essential features: 1) allowing only two types of most effective reference strings that have two most frequently occurring values of offset (i.e., displacement vector) named dual unity offset and 2) fully optimized coding of string matching parameters for maximum coding efficiency. Since at most only two offset values and corresponding reference string positions are allowed for any current string being coded, the optimal reference string searching process is extremely simple and only needs to select the best string from at most two candidates. Moreover, in the proposed approach, the value ranges of string matching parameters, i.e., the string offset vector and string length are very limited, resulting in few bits to code the two parameters and high coding efficiency. Compared with the AVS3 reference software HPM7.0 with IBC disabled, using AVS3 SCC common test condition and YUV test sequences in text and graphics with motion category, the proposed technique achieves Y average BD-rate reduction of 10.8% and 5.8% for all intra (AI) and low-delay B (LDB) configurations, respectively, at ultralow encoding and decoding complexity.

Preparing for Plastic Surgery Residency Interviews in a Virtual Era.

Preparing for Plastic Surgery Residency Interviews in a Virtual Era.

“The Show Is Not about Race’”: Custom, Screen Culture, and the Black and White Minstrel Show

AbstractIn 1967, when the BBC was faced with a petition by the Campaign Against Racial Discrimination requesting an end to the televised variety program the Black and White Minstrel Show (1958–1978), producers at the BBC, the press, and audience members collectively argued that the historic presence of minstrelsy in Britain rendered the practice of blacking up harmless. This article uses critical race theory as a useful framework for unpacking defenses that hinged on both the color blindness of white British audiences and the simultaneous existence of wider customs of blacking up within British television and film. I examine a range of “screen culture” from the 1920s to the 1970s, including feature films, home movies, newsreels, and television, that provide evidence of the existence of blackface as a type of racialized custom in British entertainment throughout this period. Efforts by organizations such as the Campaign Against Racial Discrimination, black press publications like Flamingo, and audiences of color to name blacking up and minstrelsy as racist in the late 1960s were met by fierce resistance from majority white audiences and producers, who denied their authority to do so. Concepts of color blindness or “racial innocence” thus become a useful means of examining, first, the wide-ranging existence of blacking-up practices within British screen culture; second, a broad reluctance by producers and the majority of audiences to identify this as racist; and third, the exceptional role that race played in characterizations of white audiences that were otherwise seen as historically fragile and impressionable in the face of screen content.

Perceptual Hashing With Visual Content Understanding for Reduced-Reference Screen Content Image Quality Assessment

Numerous screen content images (SCIs) have been produced to meet the needs of virtual desktop and remote display, which put forward a very urgent requirement for security and management of SCIs. Perceptual hashing is an effective way to deal with this issue. However, since SCIs are generally composed of pictures, graphics and texts, their intrinsic characteristics are different from those of natural images. Thus the previous hashing methods for natural images are not suitable for SCIs. In this article, we propose a perceptual hashing method for SCIs from the perspective of visual content understanding. Specifically, considering that the visual content understanding of SCIs mainly comes from textual regions, while the contours of text always have thinner width and higher contrast, it is decided to generate hash in the gradient field. An input screen image is first performed by some joint preprocessing operations. Then the maximum gradient magnitude and corresponding orientation information are extracted from three color channels R, G and B. Normalized histogram and local frequency coefficient features are further obtained from the maximum gradient magnitude. Finally, a hash sequence is constructed by statistics that are derived from extracted features. Experiments validated on three SCIs databases were conducted to evaluate classification between robustness and discrimination. Receiver operating characteristics (ROC) results demonstrate that the proposed method is superior to the state-of-the-art algorithms. Besides, SIQAD and SCID databases were leveraged to present the application in reduced-reference screen content image quality assessment, and comparisons show that our hashing could provide accurate predictions than other metrics.

Delonix regia a Folklore Remedy for Diabetes; Attenuates Oxidative Stress and Modulates Type II Diabetes Mellitus.

The folkloric profile of Delonix regia demonstrates that it can be used in the management of diabetes. The present study was conducted to evaluate the safety profile of the aerial part extracts of Delonix regia and their antidiabetic potential along with improvement in oxidative stress. Phytochemical screening, total phenolic, and flavonoid contents along with in-vitro antioxidant and alpha-amylase inhibitory activities were determined. HPLC analysis, acute toxicity, glucose tolerance, in-vivo antidiabetic effect along with the influence on biochemical, oxidative stress parameters, and comet assay of the active extract were performed and assessed. Total phenolic (831.6±0.002 mg/g GAE) and flavonoid (361.4±0.002 mg/g QE) contents were found to be higher in the methanolic extract. Inhibitory concentration IC50 indicated better results for the methanolic extract in DPPH (47.6μg/mL) and alpha-amylase inhibitory (14.61μg/mL) assays. HPLC analysis of the methanolic extract confirmed the presence of quercetin, gallic acid, caffeic acid, cinnamic acid, ferulic acid, and p-coumaric acid. Acute oral toxicity exhibited no mortality and morbidity during the 24h period. The methanolic extract showed better tolerance to glucose. Streptozotocin- nicotinamide (55-110 mg/kg) induced hyperglycemia declined along with improvement in hematological, biochemical parameters and oxidative stress markers (SOD, CAT, H202) in a dose-dependent manner. The maximum effect was recorded at 500mg/kg dose. Comet assay was performed for genotoxic studies and it was observed that the methanolic extract of Delonix regia showed the maximum genoprotective effect at 100μg/mL. The findings suggest that the methanolic aerial part extract of Delonix regia exhibited hypoglycemic, antioxidant, and hypolipidemic activities. The antidiabetic effect was comparable to glibenclamide suggesting its therapeutic use as a natural anti-diabetic remedy.

Focus and social contagion of environmental organization advocacy on Twitter.

Agriculture, overexploitation, and urbanization remain the major threats to biodiversity in the Anthropocene. The attention these threats garner among leading environmental nongovernmental organizations (eNGOs) and the wider public is critical in fostering the political will necessary to reverse biodiversity declines worldwide. I analyzed the advocacy of leading eNGOs on Twitter by scraping account timelines, screening content for advocacy relating to biodiversity threats and, for prevalent threats, further screening content for positive and negative emotional language with a sentiment lexicon. Twitter advocacy was dominated by the major threats of climate change and overexploitation and the minor threat of plastic pollution. The major threats of agriculture, urbanization, invasions, and pollution were rarely addressed. Content relating to overexploitation and plastic pollution was more socially contagious than other content. Increasing emotional negativity further increased social contagion, whereas increasing emotional positivity did not. Scientists, policy makers, and eNGOs should consider how narrowly focused advocacy on platforms like Twitter will contribute to effective global biodiversity conservation.

Keeping channels open or screening out? The digital practices of Baltic Russian-speakers during the Russia-Ukraine conflict

ABSTRACT Inspired by Couldry’s conceptualisation of media-related practices, the authors investigate the ways Baltic Russian-speakers manage their digital information-seeking (sources of news) practices and interaction (communication partners). Amidst the Russia-Ukraine conflict and the ensuing tensions between Russia and the West, we consider how these digital practices lead to ideological heterogeneity or homogeneity. The conflict between Russia and Ukraine has put the transnational affiliations and practices of Baltic Russophones under pressure. This paper therefore asks how the polarised political environment and securitisation of the cross-border media practices of Baltic Russian-speakers by the national political elite has shaped how individuals respond by keeping channels open or screening content out. Based on a mixed-method study of the digital practices of Russian-speakers living in Estonia and Latvia, the authors argue that practices supporting digital homophily and digital heterophily are not mutually exclusive but appear in specific configurations. The avoidance of counter-oppositional views (screening out) is not absolute but rather mixed with practices that open channels from time to time.

Phytochemical investigation and antioxidant activities of methanol extract, methanol fractions and essential oil of Dillenia suffruticosa leaves

Oxidative stress has been known as a key factor of many disorders affecting human beings. Reactive oxygen species (ROS) attack vital biomolecules, weakening their functioning, thus exacerbating diseases. To attenuate oxidative stress-associated diseases a novel approaches of antioxidant therapies have been anticipated. Antioxidants have the potential to inhibit the propagation and formation of ROS. Dillenia suffruticosa is a medicinal plant, used by the local people for the treatment of various ailments. The study aimed to evaluate the phytochemical screening, antioxidative activity, total phenolic and flavonoid contents of methanol extract, fractions and essential oil of D. suffruticosa. Furthermore, the analysis of phytochemicals was done using gas chromatography and mass spectrometry (GCMS). The result showed the existence of alkaloids, anthraquinones, flavonoids, phytosterol, saponins, tannins, triterpenoids and steroids in the methanol extract and fractions of D. suffruticosa. The butanol fraction and methanol extract showed high phenolic (379.00 ± 9.25 and 277.00 ± 3.50 mg/g) and flavonoid values (74.44 ± 2.18 and 34.83 ± 0.71 mg/g) as compared to ethyl acetate, n-hexane and chloroform fractions. The scavenging capacity of butanol fraction and methanol extract was also higher than other fractions. GCMS analysis indicated the presences of various compounds in methanol extract, fractions and essential oil including methyl glycolate, lauryl acetate, phenol, 2,4-bis (1,1-dimethylethyl), 9,12-octadecadienoic acid, hexadecanoic acid, methyl ester, methyl stearate, phenol, benzyl alcohol, 3-hexen-1-ol, acetate and phytol. Thus, methanol extract, fractions and essential oil of D. suffruticosa leaves mainly contain vital phytochemical and shows good antioxidant activity.

Pesticide poisoning deaths: a 19-year retrospective study of medicolegal autopsies in center Tunisia

BackgroundPesticide poisoning is recognized as an important public health problem worldwide, especially in the developing countries, such as Tunisia, where these products are massively used in agriculture. The objective of our study was to document the forensic deaths caused by pesticides reported from a forensic center located in the coastal region of Tunisia.MethodsThis is a 19-year retrospective descriptive study of lethal pesticide poisoning victims autopsied in the Department of Forensic Medicine at Farhat Hached University Hospital in Sousse, Tunisia, from 1991 to 2009.ResultsOne hundred thirty deaths were collected. The majority of the victims were female (62% vs 38%). The mean age was 27.46 years with the highest frequency of poisoning deaths occurring in the 21-30 years age group (34%). Eleven percent of the victims were found in a state of coma and 4.6% suffered from respiratory distress. Signs observed during the external examination of the bodies were as follows: bluish discoloration of the lips and the limbs (n = 130, 100%), leakage of urine (n = 13, 10%), foaming at the mouth or the nose (n = 66, 50.8%). The most frequent signs found during autopsies were pulmonary edema in 88.4% of the cases and multiorgan congestion in 86.9%. Toxicological screening of the stomach content was positive for pesticides in 126 cases. Intoxication was mainly caused by cholinesterase inhibitor insecticides: carbamates (50%) and organophosphorus compounds (31.5%). In 92% of cases, death was in a context of suicide.ConclusionsThis study shows that a large proportion of pesticide poisoning deaths are preventable. Prevention is, on the one side, by restricting the availability of pesticides and on the other side by promulgating more vigorous legislation concerning the manufacturing, the marketing, and the use of these products.

From aviation tourism to suborbital space tourism: A study on passenger screening and business opportunities

Due to the significant amount of cost for privately paid passenger to travel the Earth orbit and beyond, orbital space tourism (OST) is not affordable for the general public in the coming decades. Therefore, the second best could be the suborbital space tourism (SST). According to the following facts, SST could be right at the corner: in October 2017, the Saudi Arabia intended to invest 1 billion USD into Virgin Galactic; on December 11, 2019, Blue Origin's New Shepard had a wholly successful 12th flight test mission (NS-12); and then on February 13, 2020, Virgin Galactic's spaceplane SpaceShipTwo, named VSS Unity, has been successfully relocated to its commercial headquarters at Spaceport America. Referring to the possible or potential effects of reusable suborbital launch vehicle (RSLV) trajectory dynamics on the neuro-vestibular system of passenger, this paper studied and discussed the pre-flight passenger screening contents and the related business opportunities for SST. Requirements for the third class medical certificate of the Federal Aviation Administration (FAA) of the USA have been proposed as a major reference. Since the SST is a new emerging market, contents for pre-flight screening of tourist need be rigorous, but could be adjustable based on accumulated flight experience in the future. The related business opportunities, either academic or commercial, in pre-flight training, pre-flight adaption, post-flight adaption, and data analysis, are expected to form a new industry chain gradually from 2020s to 2030s or 2040s.

Correction to: A low delay rate control method for screen content coding

In the original publication, the corresponding author’s affiliation was incorrect. The correct affiliation is presented in this erratum. The author regrets this mistake.

Video Error-Resilience Research Based on Error-Resilient Screen Content

In order to make video transmission more stable, various error-resilient mechanisms are proposed on video coding in the literature. However, the redundancy mechanism behind classical redundant coding algorithms is relatively simple and is not suitable for the network environment and video content in the context of screen content sequence with multiple abrupt frames and still frames. Motivated by this, a frame-level coding selection mechanism is proposed in this paper for the error-resilience transmission of screen content, where additional code stream or redundant information is considered to improve error-resilient performance with redundant coding and acceptable video quality is obtained in the case of frame transmission error. In addition, selective allocation redundancy is conducted to take the importance of the video frame ROI (region of interest) area into account in the co-encoding process. As a result, the redundancy insertion efficiency and the reliability are improved in return. The corresponding experiments validate the effectiveness of the schemes proposed in this paper.

Hybrid Adaptive Lossless Image Compression Based on Discrete Wavelet Transform.

A new hybrid transform for lossless image compression exploiting a discrete wavelet transform (DWT) and prediction is the main new contribution of this paper. Simple prediction is generally considered ineffective in conjunction with DWT but we applied it to subbands of DWT modified using reversible denoising and lifting steps (RDLSs) with step skipping. The new transform was constructed in an image-adaptive way using heuristics and entropy estimation. For a large and diverse test set consisting of 499 photographic and 247 non-photographic (screen content) images, we found that RDLS with step skipping allowed effectively combining DWT with prediction. Using prediction, we nearly doubled the JPEG 2000 compression ratio improvements that could be obtained using RDLS with step skipping. Because for some images it might be better to apply prediction instead of DWT, we proposed compression schemes with various tradeoffs, which are practical contributions of this study. Compared with unmodified JPEG 2000, one scheme improved the compression ratios of photographic and non-photographic images, on average, by 1.2% and 30.9%, respectively, at the cost of increasing the compression time by 2% and introducing only minimal modifications to JPEG 2000. Greater ratio improvements, exceeding 2% and 32%, respectively, are attainable at a greater cost.

Research on HEVC screen content coding and video transmission technology based on machine learning

With the complexity of the 5 G network environment and the diversified requirements for video transmission, multimedia content transmission in different channel environments is a direction worth studying in order to achieve good performance of digital media content transmission systems in an open network environment. Based on the code stream structure characteristics of screen content in HEVC, this paper has proposed a joint source channel coding (JSCC) scheme to study the transmission of compressed video in wireless channels. Combined with the clustering algorithm from the field of artificial intelligence in the environment of wireless channel classification problem, the parameters of the wireless channel and the influencing factors can be used to reduce the noise and then use the FCM (Fuzzy C-Means) clustering algorithm to classify the channel environment. According to the channel status, optimize the current remaining resources and implement channel coding through LDPC codes. By analyzing and minimizing the end-to-end distortion model, the adaptive bit rate allocation further guarantees the quality of the reconstructed video.

Cost Sensitive Learning Based HEVC Screen Content Intra Coding for Mobile Devices

The distinguished features of screen contents lead to the development of the Screen Content Coding (SCC) extension of High Efficiency Video Coding (HEVC). Intra coding of HEVC-SCC has to evaluate traditional HEVC intra coding modes and additional modes for screen contents, which poses a challenge for coding such a content on mobile devices. Furthermore, the heterogeneous mobile devices have varying complexity requirements. In this paper, a flexible screen content intra coding scheme is proposed, which can trade between encoding complexity and rate-distortion performance degradation via cost sensitive learning. Taking the cost of different decisions into account, binary classifiers are designed to determine whether a particular kind of coding modes will be evaluated. By adopting the cost-proportionate weighted sampling, the proposed scheme can learn a flexible coding policy offline via reinforcement learning. Experimental results show the effectiveness of the proposed scheme.

Cross-Component Prediction in HEVC

Video coding in the YCbCr color space has been widely used, since it is efficient for compression, but it can result in color distortion due to conversion error. Meanwhile, coding in the RGB color space maintains high color fidelity, having the drawback of a substantial bitrate increase with respect to YCbCr coding. Cross-component prediction (CCP) efficiently compresses video content by decorrelating color components while keeping high color fidelity. In this scheme, the chroma residual signal is predicted from the luma residual signal inside the coding loop. This paper gives a description of the CCP scheme from several points of view, from theoretical background to practical implementation. The proposed CCP scheme has been evaluated in standardization communities and adopted into H.265/High Efficiency Video Coding (HEVC) Range Extensions. The experimental results show significant coding performance improvements for both natural and screen content video, while the quality of all color components is maintained. The average coding gains for natural video are 17% and 5% bitrate reduction in the case of intra coding and 11% and 4% in the case of inter coding for RGB and YCbCr coding, respectively, while the average increment of encoding and decoding times in the HEVC reference software implementation are 10% and 4%, respectively.