The infinitestimal operator for the semigroup of the Frobenius-Perron operator from image sequence data: Vector fields and computational measurable dynamics from movies

نویسندگان

  • N. Santitissadeekorn
  • E. M. Bollt
چکیده

We present in this paper an approach to approximate the Frobenius-Perron transfer operator from a sequence of time-ordered images, that is, a movie dataset. Unlike time-series data, successive images do not provide a direct access to a trajectory of a point in a phase space; more precisely, a pixel in an image plane. Therefore, we reconstruct the velocity field from image sequences based on the infinitesimal generator of the Frobenius-Perron operator. Moreover, we relate this problem to the well-known optical flow problem from the computer vision community and we describe a validity of using the continuity equation derived from the infinitesimal operator as a constraint equation for the optical flow problem. Once the vector field, and then a discrete transfer operator are found then, in addition, we present a graph modularity method as a tool to discover basin structure in the phase space. Together with a tool to reconstruct a velocity field, this graph-based partition method provides us a way to study transport behavior and other ergodic properties of measurable dynamical systems captured only through image sequences.

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تاریخ انتشار 2006