상세정보
학술대회
Resolving Scale Ambiguity for Monocular Visual Odometry
- 발행일
- 201311
- 출처
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2013, pp.604-608
- 협약과제
- 13MC1200, 도심, 야외 비정형 3차원 공간 실시간 인식 및 로봇주행기술 개발, 유원필
- 초록
- Scale ambiguity is an inherent problem in monocular visual odometry and SLAM. Our approach is based on common assumptions such that the ground is locally planar and its distance to a camera is constant. The assumptions are usually valid in mobile robots and vehicles moving in indoor and on-road environments. Based on the assumptions, the scale factors are derived by finding the ground in locally reconstructed 3D points. Previously, kernel density estimation with a Gaussian kernel was applied to detect the ground plane, but it generated biased scale factors. This paper proposes an asymmetric Gaussian kernel to estimate unknown scale factors accurately. The asymmetric kernel is inspired from a probabilistic modeling of inliers and outliers, that is, 3D point can comes from the ground and also other objects such as buildings and trees. We experimentally verified that our asymmetric kernel had almost twice higher accuracy than the previous Gaussian kernel. Our experiments was based on an open-source visual odometry and two kinds of public datasets. © 2013 IEEE.
- KSP 제안 키워드
- Gaussian kernel, Kernel Density Estimation, Mobile robots, Monocular visual odometry, Open source, Public Datasets, Scale Ambiguity, asymmetric kernel, ground planes(GP), probabilistic modeling, scale factor