TY - GEN
T1 - Robust Visual Loop Closure Detection with Repetitive Features
AU - Lee, Seongwon
AU - Jo, Hyung Gi
AU - Cho, Hae Min
AU - Kim, Euntai
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/20
Y1 - 2018/8/20
N2 - Loop closure detection problem is an essential issue in simultaneous localization and mapping (SLAM) problem. In particular, visual loop closure detection, which using a visual sensor, should be robust to environmental conditions like confusion caused by repeated structures. In this paper, we propose a robust visual loop closure detection algorithm through restrained repetitive features observed in repeating structures. The proposed algorithm aims to extract bag of visual words (BoVW) for each image frame with RootSIFT extraction, improve it by restrain dominantly repetitive features, calculates histogram similarity score with histogram comparing method and finally decides loop closure pair(s). Experimental results show that the proposed algorithm robustly performs loop closure detection.
AB - Loop closure detection problem is an essential issue in simultaneous localization and mapping (SLAM) problem. In particular, visual loop closure detection, which using a visual sensor, should be robust to environmental conditions like confusion caused by repeated structures. In this paper, we propose a robust visual loop closure detection algorithm through restrained repetitive features observed in repeating structures. The proposed algorithm aims to extract bag of visual words (BoVW) for each image frame with RootSIFT extraction, improve it by restrain dominantly repetitive features, calculates histogram similarity score with histogram comparing method and finally decides loop closure pair(s). Experimental results show that the proposed algorithm robustly performs loop closure detection.
KW - Bag of Visual Word (BoVW)
KW - repetitive features
KW - RootSIFT
KW - Scale Invariant Feature Transform (SIFT)
KW - Visual loop closure detection
UR - https://www.scopus.com/pages/publications/85053493957
U2 - 10.1109/URAI.2018.8441872
DO - 10.1109/URAI.2018.8441872
M3 - Conference paper
AN - SCOPUS:85053493957
SN - 9781538663349
T3 - 2018 15th International Conference on Ubiquitous Robots, UR 2018
SP - 891
EP - 895
BT - 2018 15th International Conference on Ubiquitous Robots, UR 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Ubiquitous Robots, UR 2018
Y2 - 27 June 2018 through 30 June 2018
ER -