Region of interest identification in unmanned aerial vehicle imagery

Jeffrey L. Solka; David J. Marchette; George W. Rogers; Evelyn C. Durling; John E. Green; D. Talsma

doi:10.1117/12.267823

26 February 1997 Region of interest identification in unmanned aerial vehicle imagery

Jeffrey L. Solka, David J. Marchette, George W. Rogers, Evelyn C. Durling, John E. Green, D. Talsma

Proceedings Volume 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision; (1997) https://doi.org/10.1117/12.267823
Event: 25th Annual AIPR Workshop on Emerging Applications of Computer Vision, 1996, Washington, DC, United States

Abstract

This paper details recent work by our group on the use of low-level features for the identification of man-made regions in unmanned aerial vehicle (UAV) imagery. Using low- level fractal-based features, the system classifies regions in the image via probability densities estimated for each class. These densities are estimated semi-parametrically, giving the system great flexibility in the functional form of the densities. This paper details some of our group's contributions to the areas of feature extraction, probability density estimation, classification, and the integration of these techniques into a user friendly environment. In addition we present some preliminary results from an ongoing large scale study involving recently collected UAV imagery.

Citation Download Citation

Jeffrey L. Solka, David J. Marchette, George W. Rogers, Evelyn C. Durling, John E. Green, and D. Talsma "Region of interest identification in unmanned aerial vehicle imagery", Proc. SPIE 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision, (26 February 1997); https://doi.org/10.1117/12.267823

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