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Aerial tracking of elongated objects in rural environments

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Abstract

In this paper, a new approach to finding and tracking various land cover boundaries such as rivers, agricultural fields, channels and roads for use in visual navigation system of an unmanned aerial vehicle is presented. We use a combination of statistical estimation and optimization techniques for extraction of dominant boundaries in noisy aerial images. A set of perceptual grouping restrictions is used to connect the acquired piecewise boundaries and to find the heading direction of the main boundary. The results are further refined by applying a set of texture and colour cues and eliminating any false hypothesis. To reduce the computation requirements, another approach based on sampled colour values of different land covers is also investigated. Colour characteristics of a set of manually selected windows are compared to select the best attributes needed for discrimination between different land covers in various (natural) lighting conditions. Each frame is then partially scanned and desired environmental features are extracted and classified. The results show that the proposed technique meets the minimum speed and accuracy requirement of aforementioned application and outperforms single-feature object tracking algorithms.

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Authors and Affiliations

  1. Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Melbourne, Australia

    B. Majidi & A. Bab-Hadiashar

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  1. B. Majidi
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  2. A. Bab-Hadiashar
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Correspondence to A. Bab-Hadiashar.

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Majidi, B., Bab-Hadiashar, A. Aerial tracking of elongated objects in rural environments. Machine Vision and Applications 20, 23–34 (2009). https://doi.org/10.1007/s00138-007-0102-2

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