Capturing Vivid 3D Models of the World from Video
As humans we take the ability to perceive the dynamic world around us in three dimensions for granted. From an early age we can grasp an object by adapting our fingers to its 3D shape; we can understand our mother’s feelings by interpreting her facial expressions; or we can effortlessly navigate through a busy street. All of these tasks require some internal 3D representation of shape, deformations and motion. Building algorithms that can emulate this level of human 3D perception has proved to be a much harder task than initially anticipated.
In this lecture Professor Lourdes Agapito will show progress from her early systems which captured sparse 3D models with primitive representations of deformation towards our most recent algorithms which can capture every fold and detail of hands, faces and clothes in 3D using as input video sequences taken with a single consumer camera.