We propose a new adaptive filtering algorithm whose convergence rate is very fast even for a highly correlated input signal. It is well-known that convergence rate gets worse when...
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
Illustration-inspired techniques have provided alternative ways to visualize time-varying data. Techniques such as speedlines, flow ribbons, strobe silhouettes and opacity-based t...
In this paper, we deal with imitation learning of arm movements in humanoid robots. Hidden Markov Models (HMM) are used to generalize movements demonstrated to a robot multiple tim...
One of the primary goals of undergraduate studies programs is to promote the professional and personal growth and success of their students. First year students, however, often suf...