Going Further with Point Pair Features

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.Comment: Corrected post-print of manuscript accepted to the European Conference on Computer Vision (ECCV) 2016; https://link.springer.com/chapter/10.1007/978-3-319-46487-9_5

iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects

We address the task of 6D pose estimation of known rigid objects from single input images in scenarios where the objects are partly occluded. Recent RGB-D-based methods are robust to moderate degrees of occlusion. For RGB inputs, no previous method works well for partly occluded objects. Our main contribution is to present the first deep learning-based system that estimates accurate poses for partly occluded objects from RGB-D and RGB input. We achieve this with a new instance-aware pipeline that decomposes 6D object pose estimation into a sequence of simpler steps, where each step removes specific aspects of the problem. The first step localizes all known objects in the image using an instance segmentation network, and hence eliminates surrounding clutter and occluders. The second step densely maps pixels to 3D object surface positions, so called object coordinates, using an encoder-decoder network, and hence eliminates object appearance. The third, and final, step predicts the 6D pose using geometric optimization. We demonstrate that we significantly outperform the state-of-the-art for pose estimation of partly occluded objects for both RGB and RGB-D input

Recovering 6D Object Pose: A Review and Multi-modal Analysis

A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting the depth data, the study in this paper presents thorough multi-modal analyses. It discusses the above-mentioned challenges for full 6D object pose estimation in RGB-D images comparing the performances of several 6D detectors in order to answer the following questions: What is the current position of the computer vision community for maintaining "automation" in robotic manipulation? What next steps should the community take for improving "autonomy" in robotics while handling objects? Our findings include: (i) reasonably accurate results are obtained on textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy existence of occlusion and clutter severely affects the detectors, and similar-looking distractors is the biggest challenge in recovering instances' 6D. (iii) Template-based methods and random forest-based learning algorithms underlie object detection and 6D pose estimation. Recent paradigm is to learn deep discriminative feature representations and to adopt CNNs taking RGB images as input. (iv) Depending on the availability of large-scale 6D annotated depth datasets, feature representations can be learnt on these datasets, and then the learnt representations can be customized for the 6D problem

Virtual Immortality: Reanimating Characters from TV Shows.

The objective of this work is to build virtual talking avatars of characters fully automatically from TV shows. From this unconstrained data, we show how to capture a character's style of speech, visual appearance and language in an e ort to construct an interactive avatar of the person and e ectively immortalize them in a computational model. We make three contributions (i) a complete framework for producing a generative model of the audiovisual and language of characters from TV shows; (ii) a novel method for aligning transcripts to video using the audio; and (iii) a fast audio segmentation system for silencing nonspoken audio from TV shows. Our framework is demonstrated using all 236 episodes from the TV series Friends [34] ( 97hrs of video) and shown to generate novel sentences as well as character specific speech and video

Using PROGRESS-Plus to identify current approaches to the collection and reporting of equity-relevant data: a scoping review

Objectives: Our objectives were to identify what and how data relating to the social determinants of health are collected and reported in equity-relevant studies and map these data to the PROGRESS-Plus framework. Study Design and Setting: We performed a scoping review. We ran two systematic searches of MEDLINE and Embase for equityrelevant studies published during 2021. We included studies in any language without limitations to participant characteristics. Included studies were required to have collected and reported at least two participant variables relevant to evaluating individual-level social determinants of health. We applied the PROGRESS-Plus framework to identify and organize these data. Results: We extracted data from 200 equity-relevant studies, providing 962 items defined by PROGRESS-Plus. A median of 4 (interquartile range 5 2) PROGRESS-Plus items were reported in the included studies. 92% of studies reported age; 78% reported sex/gender; 65% reported educational attainment; 49% reported socioeconomic status; 45% reported race; 44% reported social capital; 33% reported occupation; 14% reported place and 9% reported religion. Conclusion: Our synthesis demonstrated that researchers currently collect a limited range of equity-relevant data, but usefully provides a range of examples spanning PROGRESS-Plus to inform the development of improved, standardized practices.Emma L. Karrana, Aidan G. Cashina, Trevor Barker, Mark A. Boyd, Alessandro Chiarotto, Omar Dewidar, Vina Mohabir, Jennifer Petkovic Saurab Sharma, Sinan Tejani, Peter Tugwell, G. Lorimer Mosele

Multi-centre parallel arm randomised controlled trial to assess the effectiveness and cost-effectiveness of a group-based cognitive behavioural approach to managing fatigue in people with multiple sclerosis

Abstract (provisional) Background Fatigue is one of the most commonly reported and debilitating symptoms of multiple sclerosis (MS); approximately two-thirds of people with MS consider it to be one of their three most troubling symptoms. It may limit or prevent participation in everyday activities, work, leisure, and social pursuits, reduce psychological well-being and is one of the key precipitants of early retirement. Energy effectiveness approaches have been shown to be effective in reducing MS-fatigue, increasing self-efficacy and improving quality of life. Cognitive behavioural approaches have been found to be effective for managing fatigue in other conditions, such as chronic fatigue syndrome, and more recently, in MS. The aim of this pragmatic trial is to evaluate the clinical and cost-effectiveness of a recently developed group-based fatigue management intervention (that blends cognitive behavioural and energy effectiveness approaches) compared with current local practice. Methods This is a multi-centre parallel arm block-randomised controlled trial (RCT) of a six session group-based fatigue management intervention, delivered by health professionals, compared with current local practice. 180 consenting adults with a confirmed diagnosis of MS and significant fatigue levels, recruited via secondary/primary care or newsletters/websites, will be randomised to receive the fatigue management intervention or current local practice. An economic evaluation will be undertaken alongside the trial. Primary outcomes are fatigue severity, self-efficacy and disease-specific quality of life. Secondary outcomes include fatigue impact, general quality of life, mood, activity patterns, and cost-effectiveness. Outcomes in those receiving the fatigue management intervention will be measured 1 week prior to, and 1, 4, and 12 months after the intervention (and at equivalent times in those receiving current local practice). A qualitative component will examine what aspects of the fatigue management intervention participants found helpful/unhelpful and barriers to change. Discussion This trial is the fourth stage of a research programme that has followed the Medical Research Council guidance for developing and evaluating complex interventions. What makes the intervention unique is that it blends cognitive behavioural and energy effectiveness approaches. A potential strength of the intervention is that it could be integrated into existing service delivery models as it has been designed to be delivered by staff already working with people with MS. Service users will be involved throughout this research. Trial registration: Current Controlled Trials ISRCTN7651747

Cyclosporine-A-induced nephrotoxicity in children with minimal-change nephrotic syndrome: long-term treatment up to 10 years

The impact of cyclosporine A (CsA) therapy in patients with steroid-dependent nephrotic-syndrome (SDNS) on long-term renal function is controversial. Data beyond 5 years are rare. Long-term renal function was evaluated in children with SDNS with and without CsA therapy, especially beyond 5 years. Twenty children were treated with CsA (study group) for a mean of 5.4 ± 2.2 years (ten patients for 5–11 years). Glomerular filtration rate (GFR) was calculated before and after 3 and 12 months and at latest follow-up of therapy. Fifteen children with cyclophosphamide-treated SDNS without CsA served as controls. In the study group, GFR decreased within 12 months from 136 ± 19 to 120 ± 31, to 114 ± 14 ml/min per 1.73 m2 at latest follow-up (p < 0.0001). Patients with CsA > 5 years had a GFR of 111 ± 14 ml/min per 1.73 m2 at latest follow-up without a GFR below 90 ml/min per 1.73 m2. No CsA toxicity was found in biopsies. In the control group, GFR dropped within 3 months, from 137 ± 27 to 130 ± 24, to 126 ± 19 ml/min per 1.73 m2 at latest follow-up (p = 0.1). Patients with and without nephrotoxic CsA therapy showed a drop in GFR. In CsA-treated patients, GFR was about 12% lower at latest follow-up compared with patients without nephrotoxic therapy but always remained within normal range. CsA seems to be safe, even in long-term treatment for more than 5 years