We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach...
We propose a human action clustering method based on a 3D representation of the body in terms of volumetric coordinates. Features representing body postures are extracted directly...
Massimiliano Pierobon, Marco Marcon, Augusto Sarti...
This paper presents a learning based approach to tracking articulated human body motion from a single camera. In order to address the problem of pose ambiguity, a one-to-many mappi...
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...
This paper presents a novel auto-calibration method from unconstrained human body motion. It relies on the underlying biomechanical constraints associated with human bipedal locom...