A Particle Method for Finding Distributed Objects
Abstract
Detecting and identifying distributed objects in an image is a challenge with wide research application. This search problem is difficult, in part, because the individual, multipixel "spots" that make up a distributed object must be taken in the aggregate to have any relevance, and identification is possible only when the majority of the individual spots are detected and found to conform to an expected pattern. In this paper, particle filtering methods are extended in order to detect, localize, and identify a distributed object in a single cluttered image by maximizing the joint probability that a particular collection of spots is the object of interest. The method is illustrated using a "surrogate" estimation problem. Results demonstrate that the proposed method gives a high probability of correct detection and low object location error when the signal to clutter-plus-noise ratio is above 5 decibels.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2004
- Accession Number
- ADA524344
Entities
People
- John H. Greenewald
- Stanton H. Musick
- Teri L. Piatt
Organizations
- Air Force Research Laboratory