A maximum likelihood approach to speed estimation of foreground objects in video signals

Motion and speed estimation play a key role in computer vision and video processing for various application scenarios. Existing algorithms are mainly based on projected and apparent motion models and are currently used in many contexts, such as automotive security and driver assistance, industrial automation and inspection systems, video surveillance, human activity tracking and biomedical solutions, including monitoring of vital signs. In this paper, a general Maximum Likelihood (ML) approach to speed estimation of foreground objects in video streams is proposed. Application examples are presented and the performance of the proposed algorithms is discussed and compared with more conventional solutions

On Motion Analysis of Multiple Time-Variant Objects in Video Sequences

Motion analysis and speed estimation from video signals is a topic of increasing interest, e.g., in the field of traffic monitoring and road surveillance. Moving objects in a considered video sequence may undergo several modifications either due to perspectival issues, that depend on the camera placement, or periodic behaviours. Hence, geometrical transformations, such as scaling and rotations, and periodic features are often superimposed to the motion of an object of interest. In this paper we present a novel method to speed estimation that applies to video streams framing multiple objects which experience a dynamic change throughout the video duration. Applications and results are presented to assess the robustness of the proposed algorithm

Motion magnification algorithms for video-based breathing monitoring

In this paper, we present two video processing techniques for contact-less estimation of the Respiratory Rate (RR) of framed subjects. Due to the modest extent of movements related to respiration in both infants and adults, specific algorithms to efficiently detect breathing are needed. For this reason, motion-related variations in video signals are exploited to identify respiration of the monitored patient and simultaneously estimate the RR over time. Our estimation methods rely on two motion magnification algorithms that are exploited to enhance the subtle respiration-related movements. In particular, amplitude- and phase-based algorithms for motion magnification are considered to extract reliable motion signals. The proposed estimation systems perform both spatial decomposition of the video frames combined with proper temporal filtering to extract breathing information. After periodic (or quasi-periodic) respiratory signals are extracted and jointly analysed, we apply the Maximum Likelihood (ML) criterion to estimate the fundamental frequency, corresponding to the RR. The performance of the presented methods is first assessed by comparison with reference data. Videos framing different subjects, i.e., newborns and adults, are tested. Finally, the RR estimation accuracy of both methods is measured in terms of normalized Root Mean Squared Error (RMSE), demonstrating the superiority, performance-wise, of the phase-based method

Evaluation of quality parameters of orange juice stabilized by two thermal treatments (helical heat exchanger and ohmic heating) and non-thermal (high-pressure processing)

This work aims to compare the impact of three thermal (helical coil heat exchanger HCHE, ohmic heating OH, and mild pasteurization MP) and one non-thermal (high-pressure processing HPP) treatments on orange juice by using industrial plants. Nutritional (total phenolic content (TPC), ascorbic acid (AA) and total antioxidant capacity (TAC)), physical (viscosity, colour, browning index (BI) and suspended pulp (SP)), sensory (Triangle test and QDA) as well as chemical (H-1 NMR spectroscopy) aspects were analyzed. Results revealed a significant (p < 0.05) increase in viscosity for HPP (+20%) compared to untreated samples while the opposite effect was observed for all thermal treatments (-22%). The lowest a* values were observed in HPP and HCHE samples. Total phenolic content decreased significantly only in HCHE (-14%), while the highest ascorbic acid content was observed in HPP samples and it resulted not significantly different from untreated. Regarding the chemical profile, treated samples (except for MP) led to a significant (p < 0.05) decrease of all selected marker peaks, mainly including sugars (alpha- and beta-glucose, beta-fructose, and sucrose) and amino acids compared to untreated ones. HPP samples showed a similar sensory profile if compared with the untreated sample, showing only a significant difference (p < 0.05) in terms of orange aroma; on the contrary, OH, HCHE, MP rated the lowest acceptances due to, among all considered descriptors, orange aroma, cooked aroma, sweetness, cooked taste

Early indicators of lead nephropathy

non present

Eotaxin/CCL11 in idiopathic retroperitoneal fibrosis

Background Idiopathic retroperitoneal fibrosis (IRF) is a rare fibro-inflammatory disorder characterized by a periaortic tissue which often encases the ureters causing acute renal failure. IRF histology shows fibrosis and a chronic inflammatory infiltrate with frequent tissue eosinophilia. We assessed a panel of molecules promoting eosinophilia and fibrosis in IRF patients and performed an immunogenetic study. Methods Serum levels of eotaxin/CCL11, regulated and normal T-cell expressed and secreted (RANTES), granulocyte colony-stimulating factor (G-CSF), interleukin (IL)-5, platelet-derived growth factor (PDGF) and fibroblast growth factor (FGF) were measured using a multiplex assay in 24 newly diagnosed, untreated IRF patients and 14 healthy controls. Retroperitoneal biopsies (available in 8/24 patients) were histologically evaluated to assess eosinophil infiltration, whereas mast cells (MCs) were identified by immunohistochemical analysis for human tryptase. Immunohistochemistry for eotaxin/CCL11 and its receptor CCR3 was also performed. Six single nucleotide polymorphisms (SNPs) within the CCL11 gene (rs6505403, rs1860184, rs4795896, rs17735961, rs16969415 and rs17809012) were investigated in 142 IRF patients and 214 healthy controls. Results Serum levels of eotaxin/CCL11 were higher in IRF patients than in controls (P = 0.009). Eotaxin/CCL11 drives tissue infiltration of eosinophils and MCs, which can promote fibrosis. Eosinophilic infiltration was prominent (>5 cells/hpf) in five (62.5%) cases, and abundant tryptase-positive MCs were found in all cases; notably, MCs were in a degranulating state. Immunohistochemistry showed that CCL11 was highly produced by infiltrating mononuclear cells and that its receptor CCR3 was expressed by infiltrating eosinophils, MCs, lymphocytes and fibroblasts. None of the tested CCL11 SNPs showed disease association, but the TTCCAT haplotype was significantly associated with IRF (P = 0.0005). Conclusions These findings suggest that the eotaxin/CCL11-CCR3 axis is active in IRF and may contribute to its pathogenesis; the TTCCAT haplotype within the CCL11 gene is significantly associated with IRF