• Publications
  • Influence
Dynamic Textures
TLDR
We present a characterization of dynamic textures that poses the problems of modeling, learning, recognizing and synthesizing dynamic textures on a firm analytical footing. Expand
The role of vector autoregressive modeling in predictor-based subspace identification
  • A. Chiuso
  • Mathematics, Computer Science
  • Autom.
  • 1 June 2007
TLDR
A class of new and consistent closed-loop subspace identification algorithms is based on identification of a predictor model, in a way similar as prediction error methods (PEM). Expand
Structure from Motion Causally Integrated Over Time
TLDR
We describe an algorithm for reconstructing three-dimensional structure and motion causally, in real time from monocular sequences of images, when the scene contains at least 20-40 points with high contrast. Expand
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
TLDR
We present an algorithm, based on interval analysis, able to show that there exists a unique equilibrium statex∞ ∈ [x0] which is asymptotically stable. Expand
Observability of Linear Hybrid Systems
TLDR
We analyze the observability of the continuous and discrete states of continuous-time linear hybrid systems. Expand
A Bayesian approach to sparse dynamic network identification
TLDR
We introduce two new nonparametric techniques which borrow ideas from a recently introduced kernel estimator called ''stable-spline'' as well as from sparsity inducing priors which use @?"1-type penalties. Expand
Consistency analysis of some closed-loop subspace identification methods
TLDR
We study statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems. Expand
On the relation between CCA and predictor-based subspace identification.
TLDR
In this paper we study the relation between the standard CCA approach and the recently proposed subspace procedure based on predictor identification (PBSID1from now on). Expand
Recognition of human gaits
TLDR
We pose the problem of recognizing different types of human gait in the space of dynamical systems where each gait is represented Established techniques are employed to track a kinematic model of a human body in motion, and the trajectories of the parameters are used to learn a representation of a dynamical system which defines a gait. Expand
Observability and identifiability of jump linear systems
TLDR
We analyze the observability of the continuous and discrete states of a class of linear hybrid systems and characterize the set of models that produce the same output measurements. Expand
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