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Camera position estimation and feature extraction from an incomplete image of a landmark

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Abstract

In the autonomous unmanned helicopter landing problem, the position of the unmanned helicopter relative to the landmark is very important. A camera carried on the unmanned helicopter can capture an image of the landmark. In earlier research, it was reported that the camera position could be estimated by features extracted from the landmark image. However, it is necessary that the landmark image should be complete, or with only slight deficiencies, in order for this estimation process to be possible. In this article, we report on an innovative design for an estimation made from a camera position giving an incomplete single image of the landmark. An adaptive neuro-fuzzy inference system (ANFIS) is used to construct the mapping relation between the features of complete and incomplete landmark images. It will be verified that it is possible to estimate the camera position from a landmark image more than half of which is defective via the proposed method.

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References

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Author information

Authors and Affiliations

  1. Department of Management Information Systems, Far East University, No. 49 Chung Hua Road, Hsin-Shih District, Tainan City, 74448, Taiwan, ROC

    Kuo-Hsien Hsia

  2. Graduate School of Engineering Science and Technology (Doctoral Program), National Yunlin University of Science and Technology, Yunlin, Taiwan, ROC

    Shao-Fan Lien

  3. Department of Electrical Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan, ROC

    Juhng-Perng Su

Authors
  1. Kuo-Hsien Hsia
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  2. Shao-Fan Lien
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  3. Juhng-Perng Su
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Corresponding author

Correspondence to Kuo-Hsien Hsia.

Additional information

This work was presented in part at the 16th International Symposium on Artificial Life and Robotics, Oita, Japan, January 27–29, 2011

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Hsia, KH., Lien, SF. & Su, JP. Camera position estimation and feature extraction from an incomplete image of a landmark. Artif Life Robotics 16, 152–156 (2011). https://doi.org/10.1007/s10015-011-0904-1

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  • DOI: https://doi.org/10.1007/s10015-011-0904-1

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