@inproceedings{55b3afb6046b4d4ba1a26c809ada7224,
title = "GCP-SLAM: LSD-SLAM with Learning-Based Confidence Estimation",
abstract = "Astonishing progress has been made in direct monocular SLAMs in the last few years. However, most direct methods, such as large-scale direct monocular SLAM (LSD-SLAM), usually have lower camera localization accuracy than feature-based methods. To tackle this issue, this paper suggests a novel LSD-SLAM model, i.e., GCP-SLAM, by incorporating with learning-based confidence estimation. A regression forest method is used to estimate confidence and select ground control points (GCPs). The estimated confidence and GCPs are then exploited for improving depth estimation and camera localization, respectively. Experiments show that GCP-SLAM is more reliable in tracking and relocalization than LSD-SLAM.",
keywords = "Ground control points (GCPs), Localization, Monocular SLAM, Random forest",
author = "Aidi Feng and Weiqi Zhang and Zifei Yan and Wangmeng Zuo",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 8th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2017 ; Conference date: 20-11-2017 Through 24-11-2017",
year = "2018",
doi = "10.1007/978-3-319-75786-5\_22",
language = "英语",
isbn = "9783319757858",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "262--275",
editor = "Carlos Hitoshi and Manoranjan Paul and Qingming Huang",
booktitle = "Image and Video Technology - 8th Pacific-Rim Symposium, PSIVT 2017, Revised Selected Papers",
address = "德国",
}