A review of silhouette extraction algorithms for use within visual hull pipelines

© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Markerless motion capture would permit the study of human biomechanics in environments where marker-based systems are impractical, e.g. outdoors or underwater. The visual hull tool may enable such data to be recorded, but it requires the accurate detection of the silhouette of the object in multiple camera views. This paper reviews the top-performing algorithms available to date for silhouette extraction, with the visual hull in mind as the downstream application; the rationale is that higher-quality silhouettes would lead to higher-quality visual hulls, and consequently better measurement of movement. This paper is the first attempt in the literature to compare silhouette extraction algorithms that belong to different fields of Computer Vision, namely background subtraction, semantic segmentation, and multi-view segmentation. It was found that several algorithms exist that would be substantial improvements over the silhouette extraction algorithms traditionally used in visual hull pipelines. In particular, FgSegNet v2 (a background subtraction algorithm), DeepLabv3+ JFT (a semantic segmentation algorithm), and Djelouah 2013 (a multi-view segmentation algorithm) are the most accurate and promising methods for the extraction of silhouettes from 2D images to date, and could seamlessly be integrated within a visual hull pipeline for studies of human movement or biomechanics

Messiah College Biodiesel Fuel Generation Project Final Technical Report

Many obvious and significant concerns arise when considering the concept of small-scale biodiesel production. Does the fuel produced meet the stringent requirements set by the commercial biodiesel industry? Is the process safe? How are small-scale producers collecting and transporting waste vegetable oil? How is waste from the biodiesel production process handled by small-scale producers? These concerns and many others were the focus of the research preformed in the Messiah College Biodiesel Fuel Generation project over the last three years. This project was a unique research program in which undergraduate engineering students at Messiah College set out to research the feasibility of small-biodiesel production for application on a campus of approximately 3000 students. This Department of Energy (DOE) funded research program developed out of almost a decade of small-scale biodiesel research and development work performed by students at Messiah College. Over the course of the last three years the research team focused on four key areas related to small-scale biodiesel production: Quality Testing and Assurance, Process and Processor Research, Process and Processor Development, and Community Education. The objectives for the Messiah College Biodiesel Fuel Generation Project included the following: 1. Preparing a laboratory facility for the development and optimization of processors and processes, ASTM quality assurance, and performance testing of biodiesel fuels. 2. Developing scalable processor and process designs suitable for ASTM certifiable small-scale biodiesel production, with the goals of cost reduction and increased quality. 3. Conduct research into biodiesel process improvement and cost optimization using various biodiesel feedstocks and production ingredients

Messiah College Biodiesel Fuel Generation Project Final Technical Report

Many obvious and significant concerns arise when considering the concept of small-scale biodiesel production. Does the fuel produced meet the stringent requirements set by the commercial biodiesel industry? Is the process safe? How are small-scale producers collecting and transporting waste vegetable oil? How is waste from the biodiesel production process handled by small-scale producers? These concerns and many others were the focus of the research preformed in the Messiah College Biodiesel Fuel Generation project over the last three years. This project was a unique research program in which undergraduate engineering students at Messiah College set out to research the feasibility of small-biodiesel production for application on a campus of approximately 3000 students. This Department of Energy (DOE) funded research program developed out of almost a decade of small-scale biodiesel research and development work performed by students at Messiah College. Over the course of the last three years the research team focused on four key areas related to small-scale biodiesel production: Quality Testing and Assurance, Process and Processor Research, Process and Processor Development, and Community Education. The objectives for the Messiah College Biodiesel Fuel Generation Project included the following: 1. Preparing a laboratory facility for the development and optimization of processors and processes, ASTM quality assurance, and performance testing of biodiesel fuels. 2. Developing scalable processor and process designs suitable for ASTM certifiable small-scale biodiesel production, with the goals of cost reduction and increased quality. 3. Conduct research into biodiesel process improvement and cost optimization using various biodiesel feedstocks and production ingredients

Randomized Clinical Trial to Evaluate an Atrial Fibrillation Stroke Prevention Shared Decision‐Making Pathway

Background Oral anticoagulation reduces stroke and disability in atrial fibrillation (AF) but is underused. We evaluated the effects of a novel patient‐clinician shared decision‐making (SDM) tool in reducing oral anticoagulation patient's decisional conflict as compared with usual care. Methods and Results We designed and evaluated a new digital decision aid in a multicenter, randomized, comparative effectiveness trial, ENHANCE‐AF (Engaging Patients to Help Achieve Increased Patient Choice and Engagement for AF Stroke Prevention). The digital AF shared decision‐making toolkit was developed using patient‐centered design with clear health communication principles (eg, meaningful images, limited text). Available in English and Spanish, the toolkit included the following: (1) a brief animated video; (2) interactive questions with answers; (3) a quiz to check on understanding; (4) a worksheet to be used by the patient during the encounter; and (5) an online guide for clinicians. The study population included English or Spanish speakers with nonvalvular AF and a CHA2DS2‐VASc stroke score ≥1 for men or ≥2 for women. Participants were randomized in a 1:1 ratio to either usual care or the shared decision‐making toolkit. The primary end point was the validated 16‐item Decision Conflict Scale at 1 month. Secondary outcomes included Decision Conflict Scale at 6 months and the 10‐item Decision Regret Scale at 1 and 6 months as well as a weighted average of Mann–Whitney U‐statistics for both the Decision Conflict Scale and the Decision Regret Scale. A total of 1001 participants were enrolled and followed at 5 different sites in the United States between December 18, 2019, and August 17, 2022. The mean patient age was 69±10 years (40% women, 16.9% Black, 4.5% Hispanic, 3.6% Asian), and 50% of participants had CHA2DS2‐VASc scores ≥3 (men) or ≥4 (women). The primary end point at 1 month showed a clinically meaningful reduction in decisional conflict: a 7‐point difference in median scores between the 2 arms (16.4 versus 9.4; Mann–Whitney U‐statistics=0.550; P=0.007). For the secondary end point of 1‐month Decision Regret Scale, the difference in median scores between arms was 5 points in the direction of less decisional regret (P=0.078). The treatment effects lessened over time: at 6 months the difference in medians was 4.7 points for Decision Conflict Scale (P=0.060) and 0 points for Decision Regret Scale (P=0.35). Conclusions Implementation of a novel shared decision‐making toolkit (afibguide.com; afibguide.com/clinician) achieved significantly lower decisional conflict compared with usual care in patients with AF. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04096781