Motion estimation made easy: Evolution and trends in visual odometry

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.