samplepaper.pdf (3.02 MB)
Download file

RGB-D Visual Odometry via Low Order Gaussian Gradient Metrics

Download (3.02 MB)
posted on 2023-06-27, 14:35 authored by Zhigang YaoZhigang Yao, Xu An, Christophe Charrier, Christophe Rosenberger

This paper gives a direct Visual Odometry (VO) of RGB-D cameras by using features conducted with low-order  Gaussian derivative functions such as Gaussian gradient operator. By using the feature metrics locally, it improves further possibilities for sampling more reliable points from scenarios that are lack of structure or texture and is beneficial to continuous tracking. The proposed approach reaches relatively acceptable performance with a globally heuristic framework built on the general coarse-to-fine and inverse compositional estimation. Experimental results are conducted on a group of TUM datasets for validating the proposed approach.


Email Address of Submitting Author

Submitting Author's Institution

North China University of Technology

Submitting Author's Country

  • China

Usage metrics