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

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.