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Recent Advances in Computer Vision pp 305–331Cite as

Motion Estimation Made Easy: Evolution and Trends in Visual Odometry

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 804))

Abstract

With rapid advancements in the area of mobile robotics and industrial automation, a growing need has arisen towards accurate navigation and localization of moving objects. Camera-based motion estimation is one such technique which is gaining huge popularity owing to its simplicity and use of limited resources in generating motion path. In this chapter, an attempt is made to introduce this topic for beginners covering different aspects of vision-based motion estimation task. The theoretical section provides a brief on different computer vision fundamentals specific to pose estimation task followed by a systematic discussion on the visual odometry (VO) schemes under different categories. The evolution of VO schemes over last few decades is discussed under two broad categories, that is, geometric and non-geometric approaches. The geometric approaches are further detailed under three different classes, that is, feature-based, appearance-based, and a hybrid of feature and appearance based schemes. The non-geometric approach is one of the recent paradigm shift from conventional pose estimation technique and is discussed in a separate section. Towards the end, a list of different datasets for visual odometry and allied research areas are provided for a ready reference.

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Acknowledgements

This research has been supported by DRDO—Aeronautical Research and Development Board through grant-in-aid project on “Design and development of Visual Odometry System”.

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Authors and Affiliations

  1. CSIR-Central Scientific Instruments Organisation, Chandigarh, India

    Shashi Poddar & Vinod Karar

  2. Academy of Scientific Innovative Research, CSIR-CSIO Campus, Chandigarh, India

    Rahul Kottath

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  1. Shashi Poddar
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  2. Rahul Kottath
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  3. Vinod Karar
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Correspondence to Shashi Poddar .

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Editors and Affiliations

  1. Department of Computer Science, South Valley University, Luxor, Egypt

    Mahmoud Hassaballah

  2. Department of Information Technology, Zagazig University, Zagazig, Egypt

    Khalid M. Hosny

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Poddar, S., Kottath, R., Karar, V. (2019). Motion Estimation Made Easy: Evolution and Trends in Visual Odometry. In: Hassaballah, M., Hosny, K. (eds) Recent Advances in Computer Vision. Studies in Computational Intelligence, vol 804. Springer, Cham. https://doi.org/10.1007/978-3-030-03000-1_13

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