Description
“Kinetic Echoes” hinges on the process of machine vision, particularly the application of pose recognition. This technology is designed to identify human figures in images and videos, breaking down the body into a series of key points, often referred to as landmarks. Pose recognition leverages machine learning algorithms to estimate the position and orientation of these landmarks in real-time. As the dancer moves, the system continuously detects and tracks 33 landmarks spanning the entire body.
This process of pose recognition forms the basis of our data collection. It’s an intricate dance between art and science, as each movement of the performer becomes a data point, a piece of the puzzle that, when combined, forms a dynamic, evolving portrait of human expression, brought to life within the digital landscape of the point cloud. This innovative use of machine vision allows us to bridge the gap between physical movement and digital.
Mediums
Title: Kinnetic Echoes
Year of Creation: 2022
Technologies: Touchdesigner, Google’s MediaPipe Libraries, Python
Type: Generative Artwork
Print Materials: FA Archival Paper Photo Rag Metal, Wooden Frame, Glass
