2021 Volume 50 Issue 2 Pages 254-264
We propose a method for estimating camera trajectories optimally aligned with prepared environment maps and its application. We implement Direct Sparse Odometry (DSO) as real-time Visual Odometry (VO) and Structure from Motion (SfM) to build environment maps. In this process, a pose graph is created and optimized using related camera poses to calculate the alignment of all frames from DSO towards the environment map with the scales matched. Therefore, the proposed method runs solely with a monocular color camera and does not require any training datasets. We demonstrate that the proposed method is able to be used as an object-based recognition system based on the difference between a map as a prior information and the current scene observations by the user. We tested this real-time application in a laboratory environment. In addition, we conducted an experiment to evaluate the accuracy of the proposed method using an existing dataset. The results showed that the proposed method improved the accuracy of pose estimation compared to the case using only DSO.
