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Proceedings Paper

Monitoring human and vehicle activities using airborne video
Author(s): Ross Cutler; Chandra S. Shekhar; B. Burns; Rama Chellappa; Robert C. Bolles; Larry S. Davis
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Paper Abstract

Ongoing work in Activity Monitoring (AM) for the Airborne Video Surveillance (AVS) project is described. The goal for AM is to recognize activities of interest involving humans and vehicles using airborne video. AM consists of three major components: (1) moving object detection, tracking, and classification; (2) image to site-model registration; (3) activity recognition. Detecting and tracking humans and vehicles form airborne video is a challenging problem due to image noise, low GSD, poor contrast, motion parallax, motion blur, and camera blur, and camera jitter. We use frame-to- frame affine-warping stabilization and temporally integrated intensity differences to detect independent motion. Moving objects are initially tracked using nearest-neighbor correspondence, followed by a greedy method that favors long track lengths and assumes locally constant velocity. Object classification is based on object size, velocity, and periodicity of motion. Site-model registration uses GPS information and camera/airplane orientations to provide an initial geolocation with +/- 100m accuracy at an elevation of 1000m. A semi-automatic procedure is utilized to improve the accuracy to +/- 5m. The activity recognition component uses the geolocated tracked objects and the site-model to detect pre-specified activities, such as people entering a forbidden area and a group of vehicles leaving a staging area.

Paper Details

Date Published: 5 May 2000
PDF: 8 pages
Proc. SPIE 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, (5 May 2000); doi: 10.1117/12.384868
Show Author Affiliations
Ross Cutler, Univ. of Maryland/College Park (United States)
Chandra S. Shekhar, Univ. of Maryland/College Park (United States)
B. Burns, SRI International (United States)
Rama Chellappa, Univ. of Maryland/College Park (United States)
Robert C. Bolles, SRI International (United States)
Larry S. Davis, Univ. of Maryland/College Park (United States)

Published in SPIE Proceedings Vol. 3905:
28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making
William R. Oliver, Editor(s)

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