POSEter is a web application that makes dynamic typographic posters through ML5.PoseNet, p5.js, HTML5, CSS3 and JavaScript.

This collaborative project, came to life during the Fall 2023 semester in Shirley Leung’s Materiality of Machine Learning course at Parsons.

The user-friendly application prompts users to input a word, choose from four stylistic options, and utilizes nose tracking to position the letters of the word every 5 seconds. Once the poster is complete, users have the option to add it to the gallery wall, with the ability to retain pictures based on browser history.

We plan to feature POSEter in our end of semester Thesis show, as a “pop-up”, interactive photo booth experience in May 2024.