On the analysis of background subtraction techniques using Gaussian mixture models

In this paper, we conduct an investigation into background subtraction techniques using Gaussian Mixture Models (GMM) in the presence of large illumination changes and background variations. We show that the techniques used to date suffer from the trade-off imposed by the use of a common learning rate to update both the mean and variance of the component densities, which leads to a degeneracy of the variance and creates “saturated pixels”. To address this problem, we propose a simple yet effective technique that differentiates between the two learning rates, and imposes a constraint on the variance so as to avoid the degeneracy problem. Experimental results are presented which show that, compared to existing techniques, the proposed algorithm provides more robust segmentation in the presence of illumination variations and abrupt changes in background distribution

Integrating the Projective Transform with Particle Filtering for Visual Tracking

<p/> <p>This paper presents the projective particle filter, a Bayesian filtering technique integrating the projective transform, which describes the distortion of vehicle trajectories on the camera plane. The characteristics inherent to traffic monitoring, and in particular the projective transform, are integrated in the particle filtering framework in order to improve the tracking robustness and accuracy. It is shown that the projective transform can be fully described by three parameters, namely, the angle of view, the height of the camera, and the ground distance to the first point of capture. This information is integrated in the importance density so as to explore the feature space more accurately. By providing a fine distribution of the samples in the feature space, the projective particle filter outperforms the standard particle filter on different tracking measures. First, the resampling frequency is reduced due to a better fit of the importance density for the estimation of the posterior density. Second, the mean squared error between the feature vector estimate and the true state is reduced compared to the estimate provided by the standard particle filter. Third, the tracking rate is improved for the projective particle filter, hence decreasing track loss.</p

Disseminated actinomycosis treated with clindamycin

International audienceActinomycosis is a rare bacterial disease caused by Actinomyces spp., an anaerobic bacteria from the oropharynx, digestive, and female genital tracts. Initial clinical presentation often mimics malignancy, which can lead to a delay in diagnosis. Cervico-facial, genitourinary, digestive, and respiratory features are the most frequent. Few cases are reported in children and risk factors are not well known in this population. We report on the case of an 8-year-old boy with disseminated actinomycosis with cervico-facial, pulmonary, and bone involvement caused by Actinomyces israelii. The infiltrative appearance initially suggested malignancy and the patient was started on chemotherapy for presumed histiocytosis. Evaluation of subsequent tissue samples demonstrated the presence of filamentous structures consistent with fungal or filamentous bacterial infection. Prolonged culture yielded the correct diagnosis. The patient had a severe allergic reaction to piperacillin/tazobactam and was therefore transitioned to clindamycin to complete a 9-month course. This treatment, which has not been reported in children, led to a favorable clinical, biological, and radiological response, with a good clinical tolerance

Global characteristics and outcomes of SARS-CoV-2 infection in children and adolescents with cancer (GRCCC): a cohort study

Background: Previous studies have shown that children and adolescents with COVID-19 generally have mild disease. Children and adolescents with cancer, however, can have severe disease when infected with respiratory viruses. In this study, we aimed to understand the clinical course and outcomes of SARS-CoV-2 infection in children and adolescents with cancer. Methods: We did a cohort study with data from 131 institutions in 45 countries. We created the Global Registry of COVID-19 in Childhood Cancer to capture de-identified data pertaining to laboratory-confirmed SARS-CoV-2 infections in children and adolescents (&lt;19 years) with cancer or having received a haematopoietic stem-cell transplantation. There were no centre-specific exclusion criteria. The registry was disseminated through professional networks through email and conferences and health-care providers were invited to submit all qualifying cases. Data for demographics, oncological diagnosis, clinical course, and cancer therapy details were collected. Primary outcomes were disease severity and modification to cancer-directed therapy. The registry remains open to data collection. Findings: Of 1520 submitted episodes, 1500 patients were included in the study between April 15, 2020, and Feb 1, 2021. 1319 patients had complete 30-day follow-up. 259 (19·9%) of 1301 patients had a severe or critical infection, and 50 (3·8%) of 1319 died with the cause attributed to COVID-19 infection. Modifications to cancer-directed therapy occurred in 609 (55·8%) of 1092 patients receiving active oncological treatment. Multivariable analysis revealed several factors associated with severe or critical illness, including World Bank low-income or lower-middle-income (odds ratio [OR] 5·8 [95% CI 3·8–8·8]; p&lt;0·0001) and upper-middle-income (1·6 [1·2–2·2]; p=0·0024) country status; age 15–18 years (1·6 [1·1–2·2]; p=0·013); absolute lymphocyte count of 300 or less cells per mm3 (2·5 [1·8–3·4]; p&lt;0·0001), absolute neutrophil count of 500 or less cells per mm3 (1·8 [1·3–2·4]; p=0·0001), and intensive treatment (1·8 [1·3–2·3]; p=0·0005). Factors associated with treatment modification included upper-middle-income country status (OR 0·5 [95% CI 0·3–0·7]; p=0·0004), primary diagnosis of other haematological malignancies (0·5 [0·3–0·8]; p=0·0088), the presence of one of more COVID-19 symptoms at the time of presentation (1·8 [1·3–2·4]; p=0·0002), and the presence of one or more comorbidities (1·6 [1·1–2·3]; p=0·020). Interpretation: In this global cohort of children and adolescents with cancer and COVID-19, severe and critical illness occurred in one fifth of patients and deaths occurred in a higher proportion than is reported in the literature in the general paediatric population. Additionally, we found that variables associated with treatment modification were not the same as those associated with greater disease severity. These data could inform clinical practice guidelines and raise awareness globally that children and adolescents with cancer are at high-risk of developing severe COVID-19 illness. Funding: American Lebanese Syrian Associated Charities and the National Cancer Institute