Poster Index (WIP)
An interactive 3D visualization of posters from the Victoria and Albert Museum’s open API. Users can explore over 16,000 artworks by artist, place of origin, category, and dominant color.
TOOLS
D3.js, HTML, CSS, Figma
TEAM
Nour Al Safadi
SKILLS
Data Visualization, UX/UI, Visual Design
Role
Design, Animation, UX/UI
The project was originally built using p5.js and the ml5.js machine learning library to classify poster images from the Victoria and Albert Museum’s open access API. For the visualization, Three.js was used to create an interactive 3D space where posters were grouped into clusters based on their classifications, with adjustable confidence levels.
BACKGROUND
ABOUT THE DATA / DESIGN
A dark theme creates contrast, allowing the posters to take visual priority. The introductory animation offers users a structured glimpse of the poster collection and its metadata, grounding them in the system before they navigate the 3D space.
WORK IN PROGRESS
We realized the project could be stronger by clustering the posters based on user-driven filters. It’s still a work in progress.* We’re refining the 3D clustering using categorical metadata and integrating Vibrant.js to extract dominant colors from the posters.
* metadata in the intro animation are placeholders and do not reflect the correct data yet.
