Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
We investigate dynamical models of human motion that can
support both synthesis and analysis tasks. Unlike coarser
discriminative models that work well when action classes are ...
— In this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. Motion capture data is recorded in ...
In recent years, the use of inertial sensing for body motion recognition has been demonstrated. However, existing work generally focuses on upper-body movements, which involve smal...
In this paper, we tackle robust human pose recognition using unlabelled markers obtained from an optical marker-based motion capture system. A coarse-to-fine fast pose matching al...