We present a novel algorithm for tracking with ladar sensors to aid in navigation, guidance and control systems, suitable
for applications to unmanned air vehicles. The methods we employ are based on Bayesian segmentation, optical flow,
active contour and Bayesian particle tracking. The algorithm herein holds several significant advantages over
traditional tracking methods. The first step in the process is the optimal segmentation of images to enhance the targets
and extract them from background clutter and noise. The Bayesian approach to segmentation allows the use of intensity
(passive) and range (active) imagery to find targets. Optical flow generalizes and improves correlation techniques for
locating objects within a frame, allowing for aspect angle and range changes. With optical flow, we may infer relative
velocities on a pixel-by-pixel basis. Active contours are ideally suited to both target-sparse and target-rich
environments. The energy approach to determining contours allows the merging and separating of potential targets in
an automatic manner. Bayesian particle tracking techniques are used to track the contours over time. The algorithm is
tested successfully on experimental and simulated ladar data (using both intensity and range data) as well as sequences
of video imageries. The streamlined processing, from obtaining the image data (of size 805x148 pixels) to detecting the
moving target to wrapping an active contour on the target, takes less than one second of clock time and provides very
accurate predictions of the target location in future frames.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.