Key Frame Extraction for SLAM Based on Spatio-temporal Slices

Authors

Xinliang Zhang, School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China;
Li Yang, School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China;
Yunji Zhao, School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China;

Abstract

Abstract: To deal with the data redundancy and computational complexity of the mobile robot 3D visual SLAM (simultaneous localization and mapping), a key frame extraction technique based on spatio-temporal slices is proposed. Based on the analysis of the texture characteristics of the spatio-temporal slices, it yields that the motion state of the image acquisition device can be represented by the slope change of the texture. The similarity degree between two adjacent slices is measured to find out the key frame by use of the nearest neighbor pixel-matching algorithm, which can accurately describe the motion state of the device with the reduction of the redundant frames. The experimental results show that the proposed method can reduce the data redundancy in frames effectively, and presents an advantage in the localization capability and processing speed in SLAM due to the exclusion of the unnecessary computation.

Recommended Citation

Zhang, Xinliang; Yang, Li; and Zhao, Yunji (2019) "Key Frame Extraction for SLAM Based on Spatio-temporal Slices," Journal of System Simulation: Vol. 30: Iss. 5, Article 13.
DOI: 10.16182/j.issn1004731x.joss.201805013
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss5/13

First Page

1724

Revised Date

2016-09-09

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201805013

Last Page

1729

CLC

TP24

Recommended Citation

Zhang Xinliang, Li Yang, Zhao Yunji. Key Frame Extraction for SLAM Based on Spatio-temporal Slices[J]. Journal of System Simulation, 2018, 30(5): 1724-1729.

DOI

10.16182/j.issn1004731x.joss.201805013