3D morphable model fitting for low-resolution facial images

This paper proposes a new algorithm for fitting a 3D morphable face model on low-resolution (LR) facial images. We analyse the criterion commonly used by the main fitting algorithms and by comparing with an image formation model, show that this criterion is only valid if the resolution of the input image is high. We then derive an imaging model to describe the process of LR image formation given the 3D model. Finally, we use this imaging model to improve the fitting criterion. Experimental results show that our algorithm significantly improves fitting results on LR images and yields similar parameters to those that would have been obtained if the input image had a higher resolution. We also show that our algorithm can be used for face recognition in low-resolutions where the conventional fitting algorithms fail

Alternative low-cost adsorbent for water and wastewater decontamination derived from eggshellwaste: an overview

As the current global trend towards more stringent environmental standards, technical applicability and cost-effectiveness became key factors in the selection of adsorbents for water and wastewater treatment. Recently, various low-cost adsorbents derived from agricultural waste, industrial by-products or natural materials, have been intensively investigated. In this respect, the eggshells from egg-breaking operations constitute significant waste disposal problems for the food industry, so the development of value-added by-products from this waste is to be welcomed. The egg processing industry is very competitive, with low profit margins due to global competition and cheap imports. Additionally, the costs associated with the egg shell disposal (mainly on landfill sites) are significant, and expected to continue increasing as landfill taxes increase. The aim of the present review is to provide an overview on the development of low-cost adsorbents derived from eggshell by-products

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Filtering requirements for gradient-based optical flow measurement

When using a gradient-based method to determine the optical flow field for an image sequence, it is generally appreciated that some spatial pre-filtering of the images is usually needed, particularly for large motion values. How-ever the characteristics of the filter are not generally given. In this paper we analyse the motion measurement from the point of view of sampling theory. We show how an aliasing problem can arise due to under-sampling in the temporal domain, and how this problem can be alleviated by appropriate post-sampling spatial filtering. We also demonstrate a connec-tion between this filtering and the methods used to generate the spatial and temporal image intensity gradients.

Face spoofing detection based on multiple descriptor fusion using multiscale dynamic binarized statistical image features

Face recognition has been the focus of attention for the past couple of decades and, as a result, a significant progress has been made in this area. However, the problem of spoofing attacks can challenge face biometric systems in practical applications. In this paper, an effective countermeasure against face spoofing attacks based on a kernel discriminant analysis approach is presented. Its success derives from different innovations. First, it is shown that the recently proposed multiscale dynamic texture descriptor based on binarized statis- tical image features on three orthogonal planes (MBSIF-TOP) is effective in detecting spoofing attacks, showing promising perfor- mance compared with existing alternatives. Next, by combining MBSIF-TOP with a blur-tolerant descriptor, namely, the dynamic multiscale local phase quantization (MLPQ-TOP) representation, the robustness of the spoofing attack detector can be further improved. The fusion of the information provided by MBSIF-TOP and MLPQ-TOP is realized via a kernel fusion approach based on a fast kernel discriminant analysis (KDA) technique. It avoids the costly eigen-analysis computations by solving the KDA problem via spectral regression. The experimental evaluation of the proposed system on different databases demonstrates its advantages in detecting spoofing attacks in various imaging conditions, compared with the existing methods

Modelling compatibility coefficient distributions for probabilistic feature-labelling schemes

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