Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework

Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult to satisfy real-time constraints. There is a trade-off between the speed (because of model complexity) and accuracy. Inspired by the rejection cascade of Viola-Jones classifier, we decompose the Gaussian Mixture Model (GMM) into an adaptive cascade of Gaussians(CoG). We achieve a good improvement in speed without compromising the accuracy with respect to the baseline GMM model. We demonstrate a speed-up factor of 4-5x and 17 percent average improvement in accuracy over Wallflowers surveillance datasets. The CoG is then demonstrated to over the latent space representation of images of a convolutional variational autoencoder(VAE). We provide initial results over CDW-2014 dataset, which could speed up background subtraction for deep architectures.Comment: Accepted for National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2019

Towards Benchmarking Scene Background Initialization

Given a set of images of a scene taken at different times, the availability of an initial background model that describes the scene without foreground objects is the prerequisite for a wide range of applications, ranging from video surveillance to computational photography. Even though several methods have been proposed for scene background initialization, the lack of a common groundtruthed dataset and of a common set of metrics makes it difficult to compare their performance. To move first steps towards an easy and fair comparison of these methods, we assembled a dataset of sequences frequently adopted for background initialization, selected or created ground truths for quantitative evaluation through a selected suite of metrics, and compared results obtained by some existing methods, making all the material publicly available.Comment: 6 pages, SBI dataset, SBMI2015 Worksho

Predictors of Nonseroconversion to SARS-CoV-2 Vaccination in Kidney Transplant Recipients

Kidney transplant recipients (KTRs) are still at risk of severe COVID-19 disease after SARS‑CoV‑2 vaccination, especially when they have limited antibody formation. Our aim was to understand the factors that may limit their humoral response. METHODS. Our data are derived from KTRs who were enrolled in the Dutch Renal Patients COVID-19 Vaccination consortium, using a discovery cohort and 2 external validation cohorts. Included in the discovery (N = 1804) and first validation (N = 288) cohorts were participants who received 2 doses of the mRNA-1273 vaccine. The second validation cohort consisted of KTRs who subsequently received a third dose of any SARS-CoV-2 vaccine (N = 1401). All participants had no history of SARS-CoV-2 infection. A multivariable logistic prediction model was built using stepwise backward regression analysis with nonseroconversion as the outcome. RESULTS. The discovery cohort comprised 836 (46.3%) KTRs, the first validation cohort 124 (43.1%) KTRs, and the second validation cohort 358 (25.6%) KTRs who did not seroconvert. In the final multivariable model‚ 12 factors remained predictive for nonseroconversion: use of mycophenolate mofetil/mycophenolic acid (MMF/MPA); chronic lung disease, heart failure, and diabetes; increased age; shorter time after transplantation; lower body mass index; lower kidney function; no alcohol consumption; ≥2 transplantations; and no use of mammalian target of rapamycin inhibitors or calcineurin inhibitors. The area under the curve was 0.77 (95% confidence interval [CI], 0.74-0.79) in the discovery cohort after adjustment for optimism, 0.81 (95% CI, 0.76-0.86) in the first validation cohort, and 0.67 (95% CI, 0.64-0.71) in the second validation cohort. The strongest predictor was the use of MMF/MPA, with a dose-dependent unfavorable effect, which remained after 3 vaccinations. CONCLUSIONS. In a large sample of KTRs, we identify a selection of KTRs at high risk of nonseroconversion after SARS-CoV-2 vaccination. Modulation of MMF/MPA treatment before vaccination may help to optimize vaccine response in these KTRs. This model contributes to future considerations on alternative vaccination strategies

Real-time Dynamic Object Detection for Autonomous Driving using Prior 3D-Maps

International audienceLidar has become an essential sensor for autonomous driving as it provides reliable depth estimation. Lidar is also the primary sensor used in building 3D maps which can be used even in the case of low-cost systems which do not use Lidar. Computation on Lidar point clouds is intensive as it requires processing of millions of points per second. Additionally there are many subsequent tasks such as clustering, detection, tracking and classification which makes real-time execution challenging. In this paper, we discuss real-time dynamic object detection algorithms which leverages previously mapped Lidar point clouds to reduce processing. The prior 3D maps provide a static background model and we formulate dynamic object detection as a background subtraction problem. Computation and modeling challenges in the mapping and online execution pipeline are described. We propose a rejection cascade architecture to subtract road regions and other 3D regions separately. We implemented an initial version of our proposed algorithm and evaluated the accuracy on CARLA simulator

Adherence to preventive measures after SARS-CoV-2 vaccination and after awareness of antibody response in kidney transplant recipients in the Netherlands:a nationwide questionnaire study

BACKGROUND: Kidney transplant recipients (KTRs) were advised to tightly adhere to government recommendations to curb the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) because of a high risk of morbidity and mortality and decreased immunogenicity after vaccination. The aim of this study was to analyse the change in adherence to preventive measures after vaccination and awareness of antibody response, and to evaluate its effectiveness.METHODS: In this large-scale, national questionnaire study, questionnaires were sent to 3531 KTRs enrolled in the Dutch RECOVAC studies, retrospectively asking for adherence to nine preventive measures on a 5-point Likert scale before and after SARS-CoV-2 vaccination and after awareness of antibody response. Blood samples were collected 28 days after the second vaccination. Antibody response was categorised as non-responder (≤50 BAU/mL), low-responder (&gt;50 ≤ 300 BAU/mL) or high-responder (&gt;300 BAU/mL), and shared with participants as a correlate of protection. Participants of whom demographics on sex and age, blood samples and completed questionnaires were available, were included. Our study took place between February 2021 and January 2022. The primary outcome of adherence before and after vaccination was assessed between August and October 2021 and compared via the Wilcoxon signed rank sum test. Logistic regression analysis was performed to estimate the association between antibody response and non-adherence, and adherence on acquiring SARS-CoV-2 infection. This study is registered at ClinicalTrials.gov (NCT04841785).FINDINGS: In 2939 KTRs (83%) who completed the first questionnaire on adherence to preventive measures, adherence was higher before than after vaccination (4.56, IQR 4.11-4.78 and 4.22, IQR 3.67-4.67, p &lt; 0.001). Adherence after awareness of antibody response was analysed in 2399 KTRs (82%) of whom also blood samples were available, containing 949 non-responders, 500 low-responders and 950 high-responders. Compared to non-responders, low- and high-responders reported higher non-adherence. Higher adherence was associated with lower infection rates before and after vaccination (OR 0.67 [0.51-0.91], p = 0.008 and OR 0.48 [0.28-0.86], p = 0.010).INTERPRETATION: Adherence decreased after SARS-CoV-2 vaccination and in KTRs who were aware of a subsequent antibody response compared with those without. Preventive measures in this vulnerable group seem to be effective, regardless of vaccination status. This study starts a debate on sharing antibody results with the patient and future studies should elucidate whether decreased adherence in antibody responders is justified, also in view of future pandemics.FUNDING: The Netherlands Organization for Health Research and Development and the Dutch Kidney Foundation.</p

Protocol of a prospective study on the diagnostic value of transcranial duplex scanning of the substantia nigra in patients with parkinsonian symptoms

<p>Abstract</p> <p>Background</p> <p>Parkinson's disease (PD) is the second most common neurodegenerative disorder. As there is no definitive diagnostic test, its diagnosis is based on clinical criteria. Recently transcranial duplex scanning (TCD) of the substantia nigra in the brainstem has been proposed as an instrument to diagnose PD. We and others have found that TCD scanning of substantia nigra duplex is a relatively accurate diagnostic instrument in patients with parkinsonian symptoms. However, all studies on TCD so far have involved well-defined, later-stage PD patients, which will obviously lead to an overestimate of the diagnostic accuracy of TCD.</p> <p>We have therefore set out to conduct a prospective study testing the diagnostic accuracy of TCD in patients with a parkinsonism of unclear origin.</p> <p>Methods/Design</p> <p>We will enrol 250 consecutive patients, who are referred to neurology outpatient clinics of two teaching hospitals, for analysis of clinically unclear parkinsonism. Patients, whose parkinsonism is clearly diagnosable at the first visit, will be excluded from the study. All patients will undergo a TCD of the substantia nigra. As a surrogate gold standard we will use the consensus clinical diagnosis reached by two independent, blinded, movement disorder specialist neurologists after 2 years follow-up. At the time of TCD, patients will also undergo a SPECT scan of the brain.</p> <p>Discussion</p> <p>As this prospective trial enrols only patients with an early-stage parkinsonism, it will yield data on the diagnostic accuracy of TCD that is relevant to daily clinical practice: The neurologist needs a diagnostic tool that provides additional information in patients with a clinically indefinable parkinsonian syndrome. The above described observational longitudinal study was designed to explicitly study this aspect in the diagnostic process.</p> <p>Trial registration</p> <p><b>(ITRSCC) NCT00368199</b></p

Space Division Multiplexing in Optical Fibres

Optical communications technology has made enormous and steady progress for several decades, providing the key resource in our increasingly information-driven society and economy. Much of this progress has been in finding innovative ways to increase the data carrying capacity of a single optical fibre. In this search, researchers have explored (and close to maximally exploited) every available degree of freedom, and even commercial systems now utilize multiplexing in time, wavelength, polarization, and phase to speed more information through the fibre infrastructure. Conspicuously, one potentially enormous source of improvement has however been left untapped in these systems: fibres can easily support hundreds of spatial modes, but today's commercial systems (single-mode or multi-mode) make no attempt to use these as parallel channels for independent signals.Comment: to appear in Nature Photonic