Live User-guided Intrinsic Video For Static Scenes

We present a novel real-time approach for user-guided intrinsic decomposition of static scenes captured by an RGB-D sensor. In the first step, we acquire a three-dimensional representation of the scene using a dense volumetric reconstruction framework. The obtained reconstruction serves as a proxy to densely fuse reflectance estimates and to store user-provided constraints in three-dimensional space. User constraints, in the form of constant shading and reflectance strokes, can be placed directly on the real-world geometry using an intuitive touch-based interaction metaphor, or using interactive mouse strokes. Fusing the decomposition results and constraints in three-dimensional space allows for robust propagation of this information to novel views by re-projection.We leverage this information to improve on the decomposition quality of existing intrinsic video decomposition techniques by further constraining the ill-posed decomposition problem. In addition to improved decomposition quality, we show a variety of live augmented reality applications such as recoloring of objects, relighting of scenes and editing of material appearance

Unsupervised Deep Single-Image Intrinsic Decomposition using Illumination-Varying Image Sequences

Machine learning based Single Image Intrinsic Decomposition (SIID) methods decompose a captured scene into its albedo and shading images by using the knowledge of a large set of known and realistic ground truth decompositions. Collecting and annotating such a dataset is an approach that cannot scale to sufficient variety and realism. We free ourselves from this limitation by training on unannotated images. Our method leverages the observation that two images of the same scene but with different lighting provide useful information on their intrinsic properties: by definition, albedo is invariant to lighting conditions, and cross-combining the estimated albedo of a first image with the estimated shading of a second one should lead back to the second one's input image. We transcribe this relationship into a siamese training scheme for a deep convolutional neural network that decomposes a single image into albedo and shading. The siamese setting allows us to introduce a new loss function including such cross-combinations, and to train solely on (time-lapse) images, discarding the need for any ground truth annotations. As a result, our method has the good properties of i) taking advantage of the time-varying information of image sequences in the (pre-computed) training step, ii) not requiring ground truth data to train on, and iii) being able to decompose single images of unseen scenes at runtime. To demonstrate and evaluate our work, we additionally propose a new rendered dataset containing illumination-varying scenes and a set of quantitative metrics to evaluate SIID algorithms. Despite its unsupervised nature, our results compete with state of the art methods, including supervised and non data-driven methods.Comment: To appear in Pacific Graphics 201

A new method for constructing small-bias spaces from Hermitian codes

We propose a new method for constructing small-bias spaces through a combination of Hermitian codes. For a class of parameters our multisets are much faster to construct than what can be achieved by use of the traditional algebraic geometric code construction. So, if speed is important, our construction is competitive with all other known constructions in that region. And if speed is not a matter of interest the small-bias spaces of the present paper still perform better than the ones related to norm-trace codes reported in [12]

Dyslipidaemia in hypertension - are we treating enough?

Introduction: The coexistence of dyslipidaemia and hypertension results in enhanced atherosclerosis. Adequate treatment of dyslipidaemia in hypertensive patients is thus essential for reducing the burden of cardiovascular diseases.Objective: To determine the prevalence of dyslipidaemia among hypertensives and evaluate lipid treatment status of patients with dyslipidaemia in a tertiary hospital in Nigeria.Methods: This cross-sectional comparative study was done between May, 2015 and June, 2016 in a tertiary hospital in Nigeria. The serum lipid levels of adult patients with hypertension and controls without hypertension were determined. Lipid treatment status of patients with dyslipidaemia were also reviewed. Serum lipid levels were analyzed using spectrophotometric methods.Results: The study included 200 adult hypertensive patients and 100 control participants. The mean age (SD) was 56.3 (6.9) years and 54.9 (8.3) years with range 41-68 and 44-69 years for patients and controls respectively. Eighty-eight (44.0%) hypertensive patients and 23(23.5%) of the control group were found to have dyslipidaemia. Out of the 60(68.2%) patients with elevated LDL-C, 32(53.3%) had LDL-C >4.1mmol/L, out of which only 8(25%) were on antilipid medication.Conclusion: Over one-third of studied hypertensive patients had dyslipidaemia and only a quarter of those who needed antilipids were on the medication. Greater awareness is needed both in the medical and patient communities in order to effectively manage dyslipidaemic hypertension, and hence aid in ameliorating the burden of cardiovascular diseases

Composition of uroliths in a tertiary hospital in South East Nigeria

Background: Urolithiasis affects primarily the urinary tract and complications as debilitating as renal failure may develop. Determining the chemical composition of uroliths can aid management and prevention of recurrence in patients.Objective: To determine the chemical composition and anatomical distribution of uroliths in Nigeria.Methods: This descriptive cross-sectional study was conducted between March 2014 and February 2016, in a tertiary hospital in Nigeria. We reviewed the outcomes of uroliths of adult patients sent to our laboratory for chemical analyses. Samples were analyzed using simple qualitative tests.Results: 52 adult patients were included with a mean age (SD) of 46.6 (12.6) years. Males (76.9%) were more affected than females (23.1%). For both sexes, highest occurrence of stones was in bladder (85.7%). Calcium-containing stones had the highest occurrence (85.2%) and predominated in the renal, ureter and urethra, followed by struvite stones (59.5%). In the bladder, struvite stones were predominant (85.8%), with calcium-containing stones accounting for 71.4%.Conclusion: This study showed that struvite and calcium phosphate-containing stones constitute majority of uroliths in our setting with low occurrence of calcium oxalate stones. This indicates that urinary tract infection most likely plays a substantial role in the formation of uroliths in Nigerians. Modern methods of stone analysis is advocated to further define management options.Keywords: Uroliths, calcium oxalate, chemical composition, struvite, stone, calculi

Fast hashing with Strong Concentration Bounds

Previous work on tabulation hashing by Patrascu and Thorup from STOC'11 on simple tabulation and from SODA'13 on twisted tabulation offered Chernoff-style concentration bounds on hash based sums, e.g., the number of balls/keys hashing to a given bin, but under some quite severe restrictions on the expected values of these sums. The basic idea in tabulation hashing is to view a key as consisting of $c=O(1)$ characters, e.g., a 64-bit key as $c=8$ characters of 8-bits. The character domain $\Sigma$ should be small enough that character tables of size $|\Sigma|$ fit in fast cache. The schemes then use $O(1)$ tables of this size, so the space of tabulation hashing is $O(|\Sigma|)$. However, the concentration bounds by Patrascu and Thorup only apply if the expected sums are $\ll |\Sigma|$. To see the problem, consider the very simple case where we use tabulation hashing to throw $n$ balls into $m$ bins and want to analyse the number of balls in a given bin. With their concentration bounds, we are fine if $n=m$, for then the expected value is $1$. However, if $m=2$, as when tossing $n$ unbiased coins, the expected value $n/2$ is $\gg |\Sigma|$ for large data sets, e.g., data sets that do not fit in fast cache. To handle expectations that go beyond the limits of our small space, we need a much more advanced analysis of simple tabulation, plus a new tabulation technique that we call \emph{tabulation-permutation} hashing which is at most twice as slow as simple tabulation. No other hashing scheme of comparable speed offers similar Chernoff-style concentration bounds.Comment: 54 pages, 3 figures. An extended abstract appeared at the 52nd Annual ACM Symposium on Theory of Computing (STOC20

Self-supervised Outdoor Scene Relighting

Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, requiring high quality synthetic renderings to train a solution. Such renderings are synthesized using priors learned from limited data. In contrast, we propose a self-supervised approach for relighting. Our approach is trained only on corpora of images collected from the internet without any user-supervision. This virtually endless source of training data allows training a general relighting solution. Our approach first decomposes an image into its albedo, geometry and illumination. A novel relighting is then produced by modifying the illumination parameters. Our solution capture shadow using a dedicated shadow prediction map, and does not rely on accurate geometry estimation. We evaluate our technique subjectively and objectively using a new dataset with ground-truth relighting. Results show the ability of our technique to produce photo-realistic and physically plausible results, that generalizes to unseen scenes.Comment: Published in ECCV '20, http://gvv.mpi-inf.mpg.de/projects/SelfRelight

Fast Differentially Private Matrix Factorization

Differentially private collaborative filtering is a challenging task, both in terms of accuracy and speed. We present a simple algorithm that is provably differentially private, while offering good performance, using a novel connection of differential privacy to Bayesian posterior sampling via Stochastic Gradient Langevin Dynamics. Due to its simplicity the algorithm lends itself to efficient implementation. By careful systems design and by exploiting the power law behavior of the data to maximize CPU cache bandwidth we are able to generate 1024 dimensional models at a rate of 8.5 million recommendations per second on a single PC

Preparation and in vitro characterization of non-effervescent floating drug delivery system of poorly soluble drug, carvedilol phosphate

The objective of the study was to enhance the solubility of carvedilol phosphate and to formulate it into non-effervescent floating tablets using swellable polymers. Solid dispersions (SD)of carvedilol were prepared with hydrophilic carriers such as polyvinylpyrrolidone and poloxamer to enhance solubility. Non-effervescent floating tablets were prepared with a combination of optimized solid dispersions and release retarding polymers/swellable polymers such as xanthan gum and polyethylene oxide. Tablets were evaluated for physicochemical properties such as hardness, thickness and buoyancy. SD prepared with the drug to poloxamer ratio of 1:4 by melt granulation showed higher dissolution rate than all other dispersions. Formulations containing 40 mg of polyethylene oxide (C-P40) and 50 mg xanthan gum (C-X50) were found to be best, with the drug retardation up to 12 hours. Optimized formulations were characterized using FTIR and DSC and no drug and excipient interactions were detected

Retrospective analysis and modern spatiotemporal characteristics of tularemia in the territory of the West Kazakhstan and North Kazakhstan regions

Rationale. An important task is to monitor the incidence of tularemia among the population of Kazakhstan. Natural foci of this infection occupy large areas. In some regions with large numbers of rodents and ectoparasites and low vaccination coverage, human cases of tularemia have been reported.The aim of the study. To carry out retrospective analysis and to study modern spatiotemporal characteristics of tularemia in the West Kazakhstan and North Kazakhstan regions in order to improve the effectiveness of preventive measures.Materials and methods. In our work, we used public records, the results of an epizootological survey of tularemia natural foci and the official data from the Departments of Sanitary and Epidemiological Control of two regions on the human cases of tularemia in 2000–2021. We used descriptive statistics methods, relative and absolute indicators of the tularemia incidence in the population for the analysis. The phenotypic and genetic properties of the strains isolated in 2000–2021 were studied according to the guidelines.Results. A retrospective analysis of the tularemia incidence among the population of the North Kazakhstan and West Kazakhstan regions showed an improvement in the epidemic situation. Over the past 20 years, 4 human cases of tularemia have been registered in the West Kazakhstan region, while the epizootic potential was quite high; more than 300 strains of the tularemia microbe were isolated during the studied period. In the North Kazakhstan region from 2000 to 2021, 11 human cases of tularemia were registered; when studying rodents, mammals and environmental objects, single positive samples for specific tularemia antibodies and antigens were detected; no strains of tularemia microbe were isolated.Conclusion. An analysis of long-term data on the epizootic and epidemic activity of tularemia natural foci, processed using descriptive statistics and GIS technology, made it possible to identify places of long-term persistence of the tularemia agent in the natural focus of the North Kazakhstan and West Kazakhstan regions and to create an electronic map of the territories endemic for tularemia to determine the scope of preventive measures