Unsupervised Segmentation of Poisson Data

This paper describes a new approach to the analysis of Poisson point processes, in time (1D) or space (2D), which is based on the minimum description length (MDL) framework. Specifically, we describe a fully unsupervised recursive segmentation algorithm for 1D and 2D observations. Experiments illustrate the good performance of the proposed methods.

• Type: Conference
• Year: 2000
• Where: ICPR
• Authors: Robert D. Nowak, Mário A. T. Figueiredo
• Keywords: ICPR 2000, Minimum Description Length, Poisson Point Processes, Unsupervised Recursive Segmentation