Application of adaptive object recognition approach to aerial surveillance

The paper presents an application of an adaptive object recognition technique to the detection and tracking of geographical features on aerial images. The paper advocates the necessity of the continuous image analysis for the classification of changing geographical features for aerial surveillance. The introduced technique includes: 1) extraction of geographical features by texture-based image analysis, 2) model learning and closed-loop model adaptation to the perceived changes in image characteristics, 3)recognition of interested target areas, and 4) a feedback reinforcement mechanism for model adaptation. Experimental results are presented for image sequences, along a path on an aerial image established for the aerial surveillance.