Paper
25 May 2005 Performance assessment of a video-based air-to-ground multiple target tracker with dynamic sensor control
Pablo Arambel, Matthew Antone, Michael Bosse, Jeff Silver, Jon Krant, Thomas Strat
Author Affiliations +
Abstract
The goal of the DARPA Video Verification of Identity (VIVID) program is to develop an automated video-based ground targeting system for unmanned aerial vehicles. The system comprises several modules that interact with each other to support tracking of multiple targets, confirmatory identification, and collateral damage avoidance. The Multiple Target Tracking (MTT) module automatically adjusts the camera pan, tilt, and zoom to support kinematic tracking, multi-target track association, and confirmatory identification. The MTT system comprises: (i) a video processor that performs moving object detection and feature extraction, including object position and velocity, (ii) a multiple hypothesis tracker that processes video processor reports to generate and maintain tracks, and (iii) a sensor resource manager that aims the sensor to improve tracking of multiple targets. This paper presents a performance assessment of the current implementation of the MTT under several operating conditions. The evaluation is done using pre-recorded airborne video to assess the ability of the video tracker to detect and track ground moving objects over extended periods of time. The tests comprise a number of different operational conditions such as multiple targets and confusers under various levels of occlusion and target maneuverability, as well as different background conditions. The paper also describes the challenges that still need to be overcome to extend track life over long periods of time.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pablo Arambel, Matthew Antone, Michael Bosse, Jeff Silver, Jon Krant, and Thomas Strat "Performance assessment of a video-based air-to-ground multiple target tracker with dynamic sensor control", Proc. SPIE 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV, (25 May 2005); https://doi.org/10.1117/12.603046
Lens.org Logo
CITATIONS
Cited by 10 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Video processing

Target detection

Sensors

Cameras

Detection and tracking algorithms

Expectation maximization algorithms

Back to Top