Motion Layer Based Object Removal In Videos

This paper proposes a novel method to generate plausible video sequences after removing relatively large objects from the original videos. In order to maintain temporal coherence among the frames, a motion layer segmentation method is applied. Then, a set of synthesized layers are generated by applying motion compensation and region completion algorithm. Finally, a new video, in which the selected object is removed, is plausibly rendered given the synthesized layers and the motion parameters. A number of example videos are shown in the results to demonstrate the effectiveness of our method

Adaptive Region-Based Video Registration

Video registration without meta data (camera location, viewing angles, and reference DEMs) is still a challenging problem. With the aim of handling this kind of problem, this paper presents an adaptive region expansion approach to propagate the alignment process from high confidence areas (reliable salient features) to low confidence areas and to simultaneously remove outlier regions. Hence, we re-cast the image registration problem as a partitioning problem such that we determine the optimal supporting regions and their corresponding motion parameters for the registration. First, we determine sparse robust correspondences between mission and reference images by using our wide baseline algorithm. Next, starting from the seed regions, the aligned areas are expanded to the whole overlapping areas using the graph cut algorithm, which is controlled by the level set representation of the previous region shape. Consequently, a robust video registration is achieved if the scene can be represented by one homography. Furthermore, we extend this approach to multi-homography video registration problem for 3D scenes, which cannot be directly solved by the current alignment methods. Using our motion layer extraction algorithm, the mission video first is segmented into several layers, then each layer is respectively aligned to the reference image by employing the region expansion algorithm. Several examples are demonstrated in the experiments to show that our approach is effective and robust

Role of Water Vapor Content in the Effects of Aerosol on the Electrification of Thunderstorms: A Numerical Study

We explored the role of the water vapor content below the freezing level in the response of idealized supercell storm electrical processes to increased concentrations of cloud condensation nuclei (CCN). Using the Weather Research and Forecasting model coupled with parameterizations electrification and discharging, we performed 30 simulations by varying both the CCN concentration and water vapor content below the freezing level. The sensitivity simulations showed a distinct response to increased concentrations of CCN, depending on the water vapor content below the freezing level. Enhancing CCN concentrations increased electrification processes of thunderstorms and produced a new negative charge region above the main positive charge center when there were ample amounts of water vapor below the freezing level. Conversely, there were weak effects on electrification and the charge structure in numerical experiments initialized with lower water vapor content below the freezing level

Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high R0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed

Assessing the Transmissibility of the New SARS-CoV-2 Variants: From Delta to Omicron

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high R0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed

Total Lightning Flash Activity Response to Aerosol over China Area

Twelve years of measurements of aerosol optical depth (AOD), cloud fraction, cloud top height, ice cloud optical thickness and lightning flash density from 2001 to 2012 have been analyzed to investigate the effect of aerosols on electrical activity over an area of China. The results show that increasing aerosol loading inspires the convective intensity, and then increases the lightning flash density. The spatial distribution of the correlation between aerosol loading and electrical activity shows a remarkable regional difference over China. The high-correlation regions embody the positive aerosol microphysical effect on the intensity of the electrical activity, while the large-scale processes may play the main role in convection development and producing lightning in low-correlation regions

Comparative Analysis of Long-Term Variation Characteristics of SO2, NO2, and O3 in the Ecological and Economic Zones of the Western Sichuan Plateau, Southwest China

Sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) are important atmospheric pollutants that affect air quality. The long-term variations of SO2 and NO2 in 2008–2018 and O3 in 2015–2018 in the relatively less populated ecological and economic zones of Western Sichuan Plateau, Southwest China were analyzed. In 2008–2018, the variations in SO2 and NO2 in the ecological zone were not significant, but Ganzi showed a slight upward trend. SO2 decreased significantly in the economic zone, especially in Panzhihua, where NO2 changes were not obvious. From 2015 to 2018, the concentration of O3 in the ecological zone increased significantly, while the economic zone showed a downward trend. The rising trend of the concentration ratio of SO2 to NO2 in the ecological zone and the declining trend in the economic zone indicate that the energy consumption structure of these two zones is quite different. The lower correlation coefficients between NO2 and O3 in the Western Sichuan Plateau imply that the variations of O3 are mainly affected by the regional background. The effects of meteorological factors on SO2, NO2, and O3 were more obvious in the economic zone where there are high anthropometric emissions