NDLI: Sky/ground modeling for autonomous MAV flight

Content Provider	IEEE Xplore Digital Library
Author	Todorovic, S. Nechyba, M.C. Ifju, P.G.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA (Todorovic, S.; Nechyba, M.C.)
Abstract	Recently, we have implemented a computer-vision based horizon-tracking algorithm for flight stability and autonomy in micro air vehicles (MAVs) [S. M. Ettinger et al., 2002]. Occasionally, this algorithm fails in scenarios where the underlying Gaussian assumption for the sky and ground appearances is not appropriate. Therefore, in this paper, we present a general statistical image modeling framework which we have use to build prior models of the sky and ground. Once trained, these models can be incorporated into our existing horizon-tracking algorithm. Since the appearances of the sky and ground vary enormously, no single feature is sufficient for accurate modeling: as such, we rely both on color and texture as critical features in our modeling framework. Specifically, we choose hue and intensity for our color representation, and the complex wavelet transform (CWT) for our texture representation. We then use hidden Markov tree (HMT) models, which are particularly well suited for the CWT's inherent tree structure, as our underlying statistical models over our feature space. With this approach, we have achieved reliable and robust image segmentation of flight images from on-board our MAVs as well as on more difficult-to-classify sky/ground images.
Sponsorship	IEEE Robotics & Autom. Soc. Nat. Sci. Council, Taiwan, Ministr. Educ., Taiwan
Starting Page	1422
Ending Page	1427
File Size	417044
Page Count	6
File Format	PDF
ISBN	0780377362
ISSN	10504729
DOI	10.1109/ROBOT.2003.1241791
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-14
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Continuous wavelet transforms Weapons Aerospace engineering Remotely operated vehicles Wavelet transforms Tree data structures Image segmentation Wavelet analysis Automotive engineering
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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