A facial recognition digital experience for the GLAM Sector
GLAM institutions often have large collections that they are unable to display to due limited floor space. Finding a solution to make these pieces more accessible to visitors would allow more exposure of the pieces to a wider audience.
- HTML5 - CSS3 - JQUERY - JAVASCRIPT - DIGITAL NZ API - GITHUB - ADOBE ILLUSTRATOR - ADOBE PHOTOSHOP -
FacePLAY aims to provide a digital solution to create a powerful digital experience to audiences wherever they are. The platform will enable the user to learn, to be entertained and share their experiences. It will create a playful, fun way for museum visitors to experience some of the archived items in the collections. Using mobile media to attract and involve the audience in experiencing the archive pieces will create a personal connection to the archives in a fun and interactive way.
As an interactive web app designed for the GLAM sector, making the most of their digital archives, FacePLAY allows the user to photograph their face and then uses facial recognition technologies to search through the archive pieces. The user is presented with a portrait from the archives that resembles them alongside their own photo.
Linking to the DigitalNZ API, FacePLAY is able to search through a GLAM institutions archives in order to display a result to the user.
