Tracking moving targets in complex environments by fusing active and passive sensors

Ben G. Fitzpatrick; Li Liu; Yun Wang; Zhanqi Cheng

doi:10.1117/12.719507

7 May 2007 Tracking moving targets in complex environments by fusing active and passive sensors

Ben G. Fitzpatrick, Li Liu, Yun Wang, Zhanqi Cheng

Proceedings Volume 6566, Automatic Target Recognition XVII; 65660N (2007) https://doi.org/10.1117/12.719507
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Ben G. Fitzpatrick, Li Liu, Yun Wang, and Zhanqi Cheng "Tracking moving targets in complex environments by fusing active and passive sensors", Proc. SPIE 6566, Automatic Target Recognition XVII, 65660N (7 May 2007); https://doi.org/10.1117/12.719507

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Optical flow

Detection and tracking algorithms

Digital filtering

Image processing

Target detection

LIDAR

Show All Keywords

Keywords/Phrases

Search In:

Publication Years