Digitizing Dress. Expanding Possibility.
digitalization lab
The Digitalization Lab transforms how dress and objects are studied, preserved, and shared. Through advanced imaging, 3D modeling, and digital storytelling, the lab creates immersive, accessible representations that extend the life and reach of the collection. Bridging creativity and technology, the lab empowers innovative research, teaching, and public engagement while redefining what it means to archive fashion in the digital age.
fall 2024 – present
Faculty
- Hunter G. Jones, Ph.D. | Assistant Professor
- Marcy L. Koontz, Ph.D. | Associate Professor
- Kristin M. Maki, MFA | Assistant Professor
- Daniel Ronderos, M. Arch | Instructor
- Brian E. Taylor, MS | Senior Instructor
Undergraduate Researchers
- Alex Jorns | Sophomore | Mathematics | Fall 2025
- Ali Byron | Senior | Interior Design | Fall/Spring 2024-2025
- Anna ‘Wings’ Liebbe | Senior | Apparel Design | Fall 2024
faculty | peer-reviewed presentations
- Koontz, M.L., Graves, C., Maki, K.M., & Taylor, B.E. (2026, February 25-27). UNBOUND: Showcasing Interdisciplinary Discovery Through an Archive of Fashion [paper presentation]. Twentieth International Conference on Design Principles and Practices, Sapienza University of Rome, Italy. (link)
- Koontz, M.L. (2025, February 25-27). Measuring Historical Color Data with a Mobile Spectrophotometer: An Analysis of Two 1925 Real Silk Costume Color Harmony Charts [paper presentation]. Nineteenth International Conference on Design Principles and Practices, LASALLE College of the Arts, Singapore. (link)
- Maki, K.M. (2025, February 25-27). Integrating 3D Modeling Applications into Interior Design Education: A Curriculum Enhancement Approach [paper presentation]. Nineteenth International Conference on Design Principles and Practices, LASALLE College of the Arts, Singapore. (link)
- Taylor, B.E. (2025, February 25-27). Advancing Fashion Design Education With AI: Scaffolding Learning and Enhancing Curriculum Integration [paper presentation]. Nineteenth International Conference on Design Principles and Practices, LASALLE College of the Arts, Singapore. (link)
undergraduate | peer-reviewed presentations
- Jorns, A.. (2026, February 25-27). Intersecting Color Spaces: Computational Modeling of Spectrophotometric Data of Two 1910s Textile Color Cards [paper presentation]. Twentieth International Conference on Design Principles and Practices, Sapienza University of Rome, Italy. (link)
undergraduate | URCA presentations
Undergraduate Research & Creative Activity Conference
The University of Alabama
April 1-2, 2025
Evaluating Mobile 3D Modeling Applications for Museum Object Digitization: A Beta Test Using a Judith Leiber Minaudière from The Fashion Archive Collection
3D modeling has become an essential tool for documenting and preserving objects in museum collections, offering new opportunities for research, education, and digital engagement. This study explores the effectiveness of three mobile 3D modeling applications in capturing and rendering a Judith Leiber minaudière from The Fashion Archive collection. Beta tests were conducted on an iPad Pro, evaluating applications based on four key criteria: graphical user interface (GUI), production cycle efficiency, exportability, and cost. The study involved scanning the object using each app, comparing the quality of the generated model, and assessing workflow usability. Results indicate that while some applications provide intuitive interfaces and high-fidelity renders, others struggled with complex textures and reflective surfaces. Exportability varied significantly, with some apps offering seamless integration with professional software, while others had format limitations. Cost analysis highlighted trade-offs between premium features and accessibility. Findings offer insights into selecting optimal mobile solutions for museum documentation and digital preservation.
The University of Alabama Undergraduate Research and Creative Activity Award
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Ali Byron reviewing the 3D digital twin of the Judith Leiber Dragonfly minaudière in REALITYSCAN.
Digitalization in fashion collections is the comprehensive process of transforming physical fashion objects and their associated data into digital assets, aiming to preserve, document, and democratize access to fashion heritage. This process is increasingly augmented by Artificial Intelligence (AI) and technologies like color spectrophotometry.
key components of digitalization
digital preservation
- Creating high-fidelity digital replicas of objects to mitigate deterioration.
- This encompasses high-resolution photography, scanning, 3D modeling, color spectrophotometry, and detailed documentation.
color spectrophotometry
- Employing color spectrophotometers to capture precise color data of objects.
- This ensures accurate digital representation of color, which is crucial for preservation and research.
3D modeling
- Utilizing 3D scanning and modeling technologies to create precise digital representations of objects.
- This allows for detailed examination of form, texture, and construction, and can be combined with color data.
enhanced accessibility
- Expanding access to collections through online platforms for researchers, students, and the public.
- This involves creating digital archives, online exhibitions, and virtual tours.
detailed documentation
- Recording comprehensive information about each object, including materials, construction techniques, historical context, provenance, and precise color data.
AI implementation in digitalization
AI revolutionizes how fashion collections approach digitalization, adding layers of efficiency and insight:
image, 3D model, and color data analysis
- AI algorithms automatically analyze digital images, 3D models, and color spectrophotometer data to identify patterns, fabric types, construction details, potential conservation issues, and color variations.
- AI helps to clean up and refine 3D scan data, creating more accurate digital models, and can correlate color data with material type.
metadata generation
- AI automates the generation of metadata, enhancing search-ability, and discoverability.
- This includes extracting information from images, 3D models, color data, and documents to create detailed descriptions.
virtual experiences
- AI-powered VR and AR applications create immersive and interactive experiences for online visitors, with accurate color representation.
- This includes virtual mannequins, interactive displays, personalized tours, and simulated garment movement.
data analysis and research
- AI analyzes large datasets of fashion information, including 3D model data, color data, and other metadata, to identify trends, patterns, and connections.
- This provides valuable insights for researchers studying fashion history, design, and conservation.
improved search capabilities
- AI enhances search functionality by using natural language processing to understand complex queries and by analyzing the content of images, 3D models, and color data.