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Ego-motion estimation concepts, algorithms and challenges: an overview

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Abstract

Ego-motion technology holds great significance for computer vision applications, robotics, augmented reality and visual simultaneous localization and mapping. This paper is a study of ego-motion estimation basic concepts, equipment, algorithms, challenges and its real world applications. First, we provide an overview for motion estimation in general with special focus on ego-motion estimation and its basic concepts. For ego-motion estimation it’s necessary to understand the notion of independent moving objects, focus of expansion, motion field, and optical flow. Vital algorithms that are used for ego-motion estimation are critically discussed in the following section of the paper. Various camera setups and their potential weakness and strength are also studied in context of ego-motion estimation. We also briefly specify some ego-motion applications used in the real world. We conclude the paper by discussing some open problems, provide some future directions and finally summarize the entire paper in the conclusions.

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Acknowledgments

We would like to thank, Dr. Saleem Gul, Institute of Management Sciences, Peshawar, Pakistan, for providing help in structuring the research article. We also appreciate the efforts of, Dr. Muhammad Haseeb, Department of Computer Science, University of Peshawar, Pakistan.

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    Naila Habib Khan & Awais Adnan

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Khan, N.H., Adnan, A. Ego-motion estimation concepts, algorithms and challenges: an overview. Multimed Tools Appl 76, 16581–16603 (2017). https://doi.org/10.1007/s11042-016-3939-4

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