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Publication in BibTeX Format

@INPROCEEDINGS{AICPub845:1999, AUTHOR={Cutler, R. and Shekhar, C. and Burns, J. B. and Chellappa, R. and Bolles, R. and Davis, L.}, TITLE={Monitoring Human and Vehicle Activities Using Airborne Video}, BOOKTITLE={28th Applied Imagery Pattern Recognition Workshop (AIPR)}, ADDRESS={Washington, D.C}, MONTH={October}, YEAR={1999}, ABSTRACT={This paper describes ongoing work in Activity Monitoring (AM) for the Airborne Video Surveillance (AVS) project. The goal for AM is to recognize “tactically significant” activities 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 from airborne video is a challenging problem due to image noise, low GSD, poor contrast, motion parallax, motion 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-interactive procedure is utilized to improve the accuracy to +/- 5m. The activity recognition component uses the geolocated tracked objects and the site-model to detect scripted activities.} }

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