
Fatma Baytar
· Associate ProfessorVerifiedCornell University · Nutrition
Active 2012–2026
About
The provided page text does not contain specific information about Professor Fatma Baytar's research focus, background, or key contributions. It primarily describes the activities, support, and events offered by the Bronfenbrenner Center for Translational Research at Cornell University, without detailing individual faculty members' biographies.
Research topics
- Mathematics
- Computer Science
- Business
- Advertising
- Human–computer interaction
- Psychology
- Surgery
- Physical therapy
- Anatomy
- Demography
- Medicine
- Geometry
- Geology
- Orthodontics
Selected publications
Fundamentals of scan data processing during the development of textile and fashion products
Reports in development and assembly of textile products · 2026-01-15
bookOpen accessSenior authorThis guide presents the foundational materials upon which the consecutive virtual product development stages depend. It introduces the principles of digital body capture, in which human geometry and posture states are recorded through 3D and four-dimensional (4D) scanning, and focuses on the fundamentals of the standard 3D formats generated by scanning and used to transfer information about complex 3D geometries between software platforms. The guide contains step by step introduction to the basic analysis functions of the open source processing tools ParaView and MeshLab which provides option for automation of the processes by Python scripting.
Fundamentals of scan data processing
Qucosa (Saxon State and University Library Dresden) · 2026-01-01
otherOpen accessSenior authorThis guide presents the foundational materials upon which the consecutive virtual product development stages depend. It introduces the principles of digital body capture, in which human geometry and posture states are recorded through 3D and four-dimensional (4D) scanning, and focuses on the fundamentals of the standard 3D formats generated by scanning and used to transfer information about complex 3D geometries between software platforms. The guide contains step by step introduction to the basic analysis functions of the open source processing tools ParaView and MeshLab which provides option for automation of the processes by Python scripting.
Fundamentals of scan data processing during the development of textile and fashion products
TIB Repositorium · 2026-01-01
reportOpen accessSenior authorDieser Leitfaden stellt die grundlegenden Materialien vor, auf denen die aufeinanderfolgenden Phasen der virtuellen Produktentwicklung basieren. Er führt in die Prinzipien der digitalen Körpererfassung ein, bei der die Geometrie und Körperhaltung des Menschen durch 3D- und vierdimensionale (4D) Scans erfasst werden, und konzentriert sich auf die Grundlagen der Standard-3D-Formate, die durch Scannen erzeugt werden und zur Übertragung von Informationen über komplexe 3D-Geometrien zwischen Softwareplattformen verwendet werden. Der Leitfaden enthält eine schrittweise Einführung in die grundlegenden Analysefunktionen der Open-Source-Verarbeitungswerkzeuge ParaView und MeshLab, die Optionen für die Automatisierung der Prozesse durch Python-Skripte bieten.
2026-02-27
book-chapterRepresentation of physical bodies in virtual environments poses sensitivity concerns related to perceptions of body image and body satisfaction. While many online clothing retailers currently do not offer virtual try-on features, the increasing availability of mobile applications could soon make such technology available to a broader number of consumers. Furthermore, there is a growing trend toward using virtual reality (VR) glasses and VR immersion. Therefore, it is important to understand consumers’ reactions to their realistic virtual bodies and attitudes toward the virtually tried-on clothes. In this experimental study, the body satisfaction of 47 women was measured before and after they saw their three-dimensional (3D) body scan models. Results showed that women reported lower levels of satisfaction with their virtual bodies compared to their satisfaction with real bodies. Virtual body satisfaction (VBS) decreased significantly when looking at the waist, abdomen, body build, and appearance. Our study findings indicated that frequent exposure to virtual representations of her body could weaken a woman’s perception of her own body and self-esteem over time. This study brings attention to the risks of virtual try-ons and related digital technologies that may challenge the well-being of individuals and calls for further exploration.
Fashion Practice · 2025-01-02 · 1 citations
articleSenior authorExploring Pant Fit Differences Between Cisgender Men and Transmasculine People
2025-01-13
articleOpen accessSenior authorThis is an accepted article with a DOI pre-assigned that is not yet published.Transgender people face challenges finding properly fitting clothing. The usage of testosterone as a part of gender-affirming care can lead to physical changes in the body. Currently available clothing may not satisfy transgender people at the functional and aesthetic levels, especially with the prevalence of gender dysphoria related to body image. Specifically, pants designed for cisgender men often have crotch, waist, and hip curves that do not accommodate transmasculine people. To address the above issues, this present research sought to identify lower body areas where cisgender men and transmasculine people may have anthropometric differences and compare the fit experiences of transmasculine people and cisgender men with a pair of test pants.
2025-01-15
articleOpen accessSenior authorErgonomic pattern-making, based on anthropometric measurements, is essential to ensuring fit and comfort but faces challenges including cost and privacy issues. This study explores an economical way of creating patterns for pants by leveraging computer graphics and fashion e-commerce data, such as model and garment sizes, which are readily available online. In this study, 100% cotton denim jeans were selected as sample pants. Computer graphics algorithms were applied to an image of a pair of jeans to automatically detect edges from the image and generate pants patterns by calculating key measurements, such as the waist, hip, crotch, and leg openings. For evaluation, the same pair of jeans was purchased and the patterns were manually traced and digitized into Optitex PDS v.21. The resulting patterns were compared with the algorithm-generated pattern and evaluated using Clo3D v.7. The hip measurements showed the biggest difference between the two patterns, where the algorithm-generated pattern had crooked side seams. In addition, the horizontal lines (e.g., the hip and leg openings) appeared more distorted because those parts were photographed closer to the lens and displayed larger than the vertical lines. While some aspects of geometric distortion in imagery could be improved, this study presented a new method for generating patterns for jeans by synthesizing publicly available e-commerce data and computer graphics. Future studies on deep learning-based models, such as segmentation, could allow for the extraction of more precise edge points for use as critical measurement points.
The Effect of Washing Cycles on Garment Fit, Dimensional Stability, and Skewness
2025-01-14
articleOpen accessSenior authorThis study aimed to gain insights into how the increase in cleaning cycles affects the relationship between the garment fit and the fabric properties of 100% cotton t-shirts related to dimensional stability and changes in skewness. Using 3D body scanning and traditional visual assessment methods, researchers evaluated changes in dimensional stability and skewness after 1, 5, 10, 15, and 20 washes. By comparing the measurements and overlaid images obtained from scanning the body and garment before and after each washing cycle, one may assess the extent of distortion induced by washing. Results showed significant shrinkage and skewness after 20 washes, with garments reducing by two sizes. The study highlights the importance of proper care instructions and suggests strategies for consumers to extend garment lifespan, contributing to discussions on sustainable fashion and the circular economy.
Exploring Machine Learning Models to Predict Garment Fit in 3d Fit Sessions
SSRN Electronic Journal · 2025-01-01
preprintOpen accessSenior authorImplementing 3D Body Scanning Methods for Inclusive Swim Cap Design and Sizing
Lecture notes in computer science · 2025-01-01
book-chapter1st authorCorresponding
Recent grants
Frequent coauthors
- 18 shared
Mona Maher
Cornell University
- 12 shared
Katarina Goodge
Cornell University
- 11 shared
Jenny Leigh Du Puis
New York State University College of Human Ecology
- 11 shared
Margaret W. Frey
Cornell University
- 9 shared
Adriana Gorea
University of Delaware
- 8 shared
Eulanda A. Sanders
- 6 shared
Wenjia Zong
Cornell University
- 5 shared
Jenine Marie Hillaire
Education
- 2011
Ph.D., Fiber Science and Apparel Design
Cornell University
Awards & honors
- National Science Foundation (NSF) CAREER Award
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
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