Pixel-Wise Prediction based Visual Odometry via Uncertainty Estimation
Journal
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Part Of
Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023
Journal Volume
108
Start Page
2517
End Page
2527
ISBN (of the container)
978-166549346-8
Date Issued
2023-01
Author(s)
Abstract
This paper introduces pixel-wise prediction based visual odometry (PWVO), which is a dense prediction task that evaluates the values of translation and rotation for every pixel in its input observations. PWVO employs uncertainty estimation to identify the noisy regions in the input observations, and adopts a selection mechanism to integrate pixel-wise predictions based on the estimated uncertainty maps to derive the final translation and rotation. In order to train PWVO in a comprehensive fashion, we further develop a data generation workflow for generating synthetic training data. The experimental results show that PWVO is able to deliver favorable results. In addition, our analyses validate the effectiveness of the designs adopted in PWVO, and demonstrate that the uncertainty maps estimated by PWVO is capable of capturing the noises in its input observations.
Event(s)
23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023
Publisher
IEEE
Type
conference paper