Paper
17 July 1998 Detection and tracking of small targets in aerial image sequences under unknown sensor motion
Thomas Fechner, Rainer Hach, Oliver Rockinger, Andreas Stenger, Peter Knappe, Christoph Stahl
Author Affiliations +
Abstract
Automatic Target Recognition is typically based on single frame image processing. In this paper we report about our work in improving ATR performance by the exploitation of image sequences using a combination of target detection and tracking. The proposed detection/tracking system consists of three subsystems: (1) the target detection module which is based on a combination of multiresolution neural network target filters which are combined by a probabilistic belief network; (2) the sensor motion compensation system which generates a dense velocity field over the actual image frame, thus estimating the effect of the unknown sensor platform motion in image coordinates and (3) a multi-target-tracker which associates existing target tracks with new observations. By the hand of real world examples we show that the combined detection/tracking method overcomes the problem of spurious false alarms generated by the single frame target detector.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Fechner, Rainer Hach, Oliver Rockinger, Andreas Stenger, Peter Knappe, and Christoph Stahl "Detection and tracking of small targets in aerial image sequences under unknown sensor motion", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); https://doi.org/10.1117/12.327102
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KEYWORDS
Target detection

Neural networks

Automatic target recognition

Image filtering

Image fusion

Optical flow

Sensors

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