We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on varying lighting conditions, ii) an evaluation methodology with a pose-error function that deals with pose ambiguities, iii) a comprehensive evaluation of 15 diverse recent methods that captures the status quo of the field, and iv) an online evaluation system that is open for continuous submission of new results. The evaluation shows that methods based on point-pair features currently perform best, outperforming template matching methods, learning-based methods and methods based on 3D local features. The project website is available at bop.felk.cvut.cz.

Diabetes mellitus (DM) is a global epidemic and affects populations in both developing and developed countries, with differing health care and resource levels. Diabetic retinopathy (DR) is a major complication of DM and a leading cause of vision loss in working middle-aged adults. Vision loss from DR can be prevented with broad-level public health strategies, but these need to be tailored to a country's and population's resource setting. Designing DR screening programs, with appropriate and timely referral to facilities with trained eye care professionals, and using cost-effective treatment for vision-threatening levels of DR can prevent vision loss. The International Council of Ophthalmology Guidelines for Diabetic Eye Care 2017 summarize and offer a comprehensive guide for DR screening, referral and follow-up schedules for DR, and appropriate management of vision-threatening DR, including diabetic macular edema (DME) and proliferative DR, for countries with high- and low- or intermediate-resource settings. The guidelines include updated evidence on screening and referral criteria, the minimum requirements for a screening vision and retinal examination, follow-up care, and management of DR and DME, including laser photocoagulation and appropriate use of intravitreal anti-vascular endothelial growth factor inhibitors and, in specific situations, intravitreal corticosteroids. Recommendations for management of DR in patients during pregnancy and with concomitant cataract also are included. The guidelines offer suggestions for monitoring outcomes and indicators of success at a population level.

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Pose estimation of free-form objects is a crucial task towards flexible and reliable highly complex autonomous systems. Recently, methods based on range and RGB-D data have shown promising results with relatively high recognition rates and fast running times. On this line, this paper presents a feature-based method for 6D pose estimation of rigid objects based on the Point Pair Features voting approach. The presented solution combines a novel preprocessing step, which takes into consideration the discriminative value of surface information, with an improved matching method for Point Pair Features. In addition, an improved clustering step and a novel view-dependent re-scoring process are proposed alongside two scene consistency verification steps. The proposed method performance is evaluated against 15 state-of-the-art solutions on a set of extensive and variate publicly available datasets with real-world scenarios under clutter and occlusion. The presented results show that the proposed method outperforms all tested state-of-the-art methods for all datasets with an overall 6.6% relative improvement compared to the second best method.

The Point Pair Feature [4] has been one of the most successful 6D pose estimation method among model-based approaches as an efficient, integrated and compromise alternative to the traditional local and global pipelines. During the last years, several variations of the algorithm have been proposed. Among these extensions, the solution introduced by Hinterstoisser et al. [6] is a major contribution. This work presents a variation of this PPF method applied to the SIXD Challenge datasets presented at the 3rd International Workshop on Recovering 6D Object Pose held at the ICCV 2017. We report an average recall of 0.77 for all datasets and overall recall of 0.82, 0.67, 0.85, 0.37, 0.97 and 0.96 for hinterstoisser, tless, tudlight, rutgers, tejani and doumanoglou datasets, respectively.

Both regimens showed a good clinical efficacy, but CyA seems to be a better glucocorticoid-sparing agent than AZA.

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BACKGROUND: Advanced glycation end-products (AGEs) are one of the mechanisms related to diabetic vascular complications. However, since AGEs are multiple and heterogeneous moieties, there is no universally accepted method to measure them for clinical purposes. The aim of this work was to study the utility of a simple fluorimetric assay as predictor of complications. METHODS: Blood samples from 102 type 2 diabetic patients were obtained to assess glucose, glycosylated haemoglobin, creatinine, lipoproteins and C Reactive Protein (CRP), fluorescent AGES by spectrophotofluorimetry and non-fluorescent AGEs by measurement of N(ε)-carboxymethyl-Lysine (CML) using an ELISA kit in a subsample of 82 patients. Urinary fluorescent AGEs, albumin and creatinine were also measured in a morning urine sample. Microvascular complications were studied by ophthalmologic examination, albuminuria and peripheral nerve conduction velocity. RESULTS: Patients without microvascular complications had significantly lower levels of both serum and urinary AGEs. CML was associated with retinopathy. Multiple regression analysis confirmed that AGEs, length of diabetes and glycosylated haemoglobin were all variables associated with diabetic complications, in this sample. CONCLUSIONS: A simple fluorimetric assay to measure low molecular weight fluorescent AGEs, and CML could be employed as screening tools to predict diabetic complications, at a primary care setting. AGEs should probably be considered as another therapeutic target in diabetes management