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Intelligent and Efficient Electrical Systems pp 231–240Cite as

Egomotion Estimation Using Background Feature Point Matching in OpenCV Environment

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 446))

Abstract

Autonomous systems are generally equipped with multiple sensor (such as radar, ultrasonic, IMU (Inertial Measurement Units), cameras, and GPS) assembly. Under complex scenarios, control of unmanned systems in GPS denied environment that depends on a quick estimate of their current position in space using cameras. Cameras provide information similar to human vision with an advantage of small construction space at low cost. Thus, estimating a camera’s egomotion from an image sequence helps to overcome these practical difficulties of autonomous camera control. The main disadvantage of using cameras under dynamic environments includes unwanted movement and jittering in the captured data, which causes a consequence in embedded vision applications. In this paper, we described an algorithm of feature-based high frame rate egomotion estimation with gradient projection and Gabor wavelet transform, which is capable of computing real-time computer vision applications. Here, the reliable singularity points were extracted through gradient projection for reducing the processing time, and egomotion was derived by applying RANSAC. The simulation was carried out in OpenCV environment, and the results demonstrate the efficiency of the proposed technique.

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Acknowledgements

The authors are grateful to the Department of Science and Technology for the award of a DST-INSPIRE Fellowship to carry out this research work.

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Authors and Affiliations

  1. Central Instrumentation and Service Laboratory, University of Madras, Chennai, India

    Sharmila Bakthavachalam & Nedumaran Damodaran

Authors
  1. Sharmila Bakthavachalam
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  2. Nedumaran Damodaran
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Correspondence to Nedumaran Damodaran .

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Editors and Affiliations

  1. Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India

    M.C. Bhuvaneswari

  2. Anora LLC, Plano, Texas, USA

    Jayashree Saxena

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Sharmila Bakthavachalam, Damodaran, N. (2018). Egomotion Estimation Using Background Feature Point Matching in OpenCV Environment. In: Bhuvaneswari, M., Saxena, J. (eds) Intelligent and Efficient Electrical Systems. Lecture Notes in Electrical Engineering, vol 446. Springer, Singapore. https://doi.org/10.1007/978-981-10-4852-4_22

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  • DOI: https://doi.org/10.1007/978-981-10-4852-4_22

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  • Online ISBN: 978-981-10-4852-4

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