Key Frame Extraction for SLAM Based on Spatio-temporal Slices

doi:10.16182/j.issn1004731x.joss.201805013

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.

Key words: SLAM, key frame, spatio-temporal slices, nearest neighbor pixel-matching algorithm

CLC Number:

TP24

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.

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