A Knowledge-Based Approach to the Detection, Tracking and Classification of Target Formations in Infrared Image Sequences

Abstract

A knowledge-based approach to the detection, tracking, and classification of ground-based formations of point targets in sequences of digitized forward-looking infrared (FLIR) image sequences is presented. The system has two components: a point target detector and tracker (PTD) which processes the image sequences and supplies candidate point targets to the knowledge-based target formation detector for clustering into formations, which are then classified as linear, V, and the like. The system has been implemented in software written in C and Common Lisp and evaluated on a variety of FLIR image sequences. The results indicate that, in all cases, the knowledge base improves system performance over that attained by the PTD alone.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cite

Text

Bronskill et al. "A Knowledge-Based Approach to the Detection, Tracking and Classification of Target Formations in Infrared Image Sequences." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989. doi:10.1109/CVPR.1989.37843

Markdown

[Bronskill et al. "A Knowledge-Based Approach to the Detection, Tracking and Classification of Target Formations in Infrared Image Sequences." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1989.](https://mlanthology.org/cvpr/1989/bronskill1989cvpr-knowledge/) doi:10.1109/CVPR.1989.37843

BibTeX

@inproceedings{bronskill1989cvpr-knowledge,
  title     = {{A Knowledge-Based Approach to the Detection, Tracking and Classification of Target Formations in Infrared Image Sequences}},
  author    = {Bronskill, John F. and Hepburn, John S. A. and Au, Wing K.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1989},
  pages     = {153-158},
  doi       = {10.1109/CVPR.1989.37843},
  url       = {https://mlanthology.org/cvpr/1989/bronskill1989cvpr-knowledge/}
}