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We're divided our research into two categories:
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The effectiveness of digital scanning​ - see below
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Deriving body composition and health metrics from 3D body scanning - click here to review
The Effectiveness of Digital Body Scanning
Real-time scan checking through machine learning
Objective: The document discusses "CHECKER," a real-time scan quality checking system designed to enhance the user experience in mobile 3D body scanning. Developed by Size Stream, the system uses machine learning to identify and correct scan errors during the scanning process including obscured body parts, improper attire, and pose errors.
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Implications: "Checker" aids in the delivery of improved pose guidance to scan subjects, enabling more error-free scans, greater clarity on how to perform a successful scan, and the acquisition of better data and a superior scan experience for users.
Matthew S. Gilmer, Steven C. Hauser, David Bruner (October 2023) "Checker: Real-time Scan Quality Checking and Associated User Experience". 3DBODY Tech Conference & Expo
Real-time scan checking through machine learning
Objective: The paper aims to showcase advancements in mobile 3D body scanning and measurement technologies developed by Size Stream. These advancements focus on improving accuracy, efficiency, and user experience through innovations in machine learning, computer vision, and body reconstruction algorithms. The ultimate goal is to provide precise body measurements for applications in custom garment construction, virtual try-ons, and health and fitness monitoring.
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Implications: The innovations presented position mobile 3D body scanning as a transformative tool for industries reliant on precise body data, offering cost-effective, user-friendly solutions for diverse applications.
Steven C. Hauser, Matthew S. Gilmer, David Bruner (October 2023) "Improvements in Mobile 3D Body Scanning and Body Measurement". 3DBODY Tech Conference & Expo
Accuracy of a Low-Cost 2D Optical Imaging System
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Objective: The paper evaluates the accuracy of a low-cost 2D optical imaging system, the MS-1 (Size Stream), compared to professional-grade 3D scanners and traditional anthropometry methods (tape measurements). It aims to validate the system’s potential for automated anthropometry in research and clinical settings, focusing on its ability to assess body size, shape, and health risks.
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Implications: The study underscores the potential of low-cost 2D imaging systems to complement existing anthropometry methods, bridging the gap between affordability and clinical utility.
C. McCarthy, Jasmine Brown, Kori Murray, S. Heymsfield (July 2023)
Precision of Digital Anthropometry Through 3D Mobile Scanning
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Objective: The article evaluates the precision of digital anthropometry through 3-dimensional (3D) scanning. Historical methods using large, expensive, non-portable systems has been well established. This study explores the comparative performance of modern mobile applications.
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Implications: A mobile 3D scanning app that uses full rotation of subjects around a smartphone camera showed similar reliability to larger, more expensive 3D scanners. However, a mobile app using just two 2D images had larger errors, though still acceptable for certain uses.
Grant M. Tinsley, Christian Rodriguez, Madelin R. Siedler, Ethan Tinoco, Sarah J. White, Christian LaValle, Alexandra Brojanac, Brielle DeHaven, Jaylynn Rasco, Christine M. Florez, and Austin J. Graybeal (March 2023)
European Journal of Clinical Nutrition
Evaluation of Automated Anthropometrics Produced by Smartphone-based Machine Learning
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Objective: The study evaluates the accuracy and reliability of smartphone-based automated anthropometric assessments compared to traditional tape measurements. It aims to determine whether mobile applications using machine learning can provide precise estimates of waist and hip circumference (WC, HC), waist-to-hip ratio (WHR), and waist-to-height ratio (W:HT) for health assessments, especially in populations with limited access to clinical care.
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Implications: The study highlights the potential of mobile-based anthropometrics but also emphasizes the need for further refinements to ensure consistent accuracy across different populations and body types.
Austin J. Graybeal, Caleb F Brandner, Grant M. Tinsley (January 2023)
National Library of Medicine - National Center for Biotechnical Information​
Validity and Reliability of a Mobile Digital Imaging Analysis
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Objective: The aim of this study was to assess the precision and agreement of a DIA application with developmental software trained by a 4-compartment (4C) model using an actual 4C model as the criterion method.
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Implications: DIA applications trained by a 4C model are reliable and produce body composition estimates equivalent with an actual 4C model.
Austin J. Graybeal, Caleb F Brandner, Grant M. Tinsley (December 2022)
"Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model".
National Library of Medicine - National Center for Biotechnical Information​
Anthropometric Evaluation of a 3D Scanning Mobile Application
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Objective: The study aims to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20-camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites.
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Implications: Three-dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). These proof-of-concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale.
Brooke Smith, Cassidy McCarthy, Marcelline E. Dechenaud, Michael C. Wong, John Shepherd, Steven B. Heymsfield (May 2022)
"Anthropometric evaluation of a 3D scanning mobile application".
Obesity A Research Journal​
Man vs. Machine: Measuring People for the Apparel Industry
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Objective: The paper compares manual body measurements taken by skilled apparel professionals with those obtained from a Size Stream SS20 3D body scanner. The goal is to assess the reliability (precision and repeatability) and compatibility (accuracy and agreement) of these two methods. By analyzing over 60 subjects and applying statistical methods, the study aims to determine whether 3D body scanning can match or surpass traditional manual measurements in the apparel industry.
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Implications: The study confirms that 3D body scanning is more precise and reliable than traditional manual measurement techniques. While some adjustments are needed to align scanning outputs with manual methods, the technology presents a viable, cost-effective, and scalable solution for the apparel industry and beyond.
Warren P. Wright (October 2019)
"Anthropometric evaluation of a 3D scanning mobile application".
3DBODY Tech Conference & Expo​
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