Abstract
Visual odometry (VO) is the process of estimating the ego-motion of an agent sequentially (e.g. vehicle, human, and robot) using only the input of single or multiple cameras attached to it. VO plays an important role in Simultaneous Localization and Mapping (SLAM), which has been widely applied in many fields. The development of VO would greatly promote the transition of visual mapping and navigation to the industry. This paper focuses on direct methods and aims to summarize recent direct algorithms from technical views. Image representation and frame matching strategy are the two key components of VO. This paper is organized based on these two aspects. A qualitative analysis of existing work is then presented. This paper simultaneously serves as a position and tutorial paper.
Highlights
As the fundamental building blocks for many emerging technologies – from autonomous cars and UAVs to virtual and augmented reality, real-time methods for Simultaneous Localization and Mapping (SLAM) and Visual odometry (VO) have made significant progress
By directly operating on the raw pixel intensity, it is believed by some researchers [2] that the main limitation of direct methods is their reliance on the consistent appearance between the matched pixels, which is seldom satisfied in robotic applications
[1] Combined binary feature descriptors and direct tracking framework to obtain robust performance, which enabled visual odometer to be applied to low-textured and poorly lit environment. [3,4] simulated the illumination changing with the gain+bias model
Summary
Visual odometry (VO) is the process of estimating the ego-motion of an agent sequentially (e.g. vehicle, human, and robot) using only the input of single or multiple cameras attached to it. VO plays an important role in Simultaneous Localization and Mapping (SLAM), which has been widely applied in many fields. The development of VO would greatly promote the transition of visual mapping and navigation to the industry. This paper focuses on direct methods and aims to summarize recent direct algorithms from technical views. Image representation and frame matching strategy are the two key components of VO. This paper is organized based on these two aspects. A qualitative analysis of existing work is presented. This paper simultaneously serves as a position and tutorial paper
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