Method

Feature Point Based Stereo-SLAM for Dynamic Scenes [st] [FPS-DS-SLAM]


Submitted on 11 Nov. 2020 02:45 by
Shubhendu Ranadive (Waseda University)

Running time:0.07 s
Environment:2 core @ 2.5 Ghz (Python & C/C++)

Method Description:
Stereo-SLAM method built upon ORB-SLAM2 for
detecting dynamic objects in the scene and removing
feature points from them for better pose
estimation.
Parameters:
ORBextractor.nFeatures: 2000
ORBextractor.scaleFactor: 1.2
ORBextractor.nLevels: 8
ORBextractor.iniThFAST: 12
ORBextractor.minThFAST: 7
Latex Bibtex:

Detailed Results

From all test sequences (sequences 11-21), our benchmark computes translational and rotational errors for all possible subsequences of length (5,10,50,100,150,...,400) meters. Our evaluation ranks methods according to the average of those values, where errors are measured in percent (for translation) and in degrees per meter (for rotation). Details for different trajectory lengths and driving speeds can be found in the plots underneath. Furthermore, the first 5 test trajectories and error plots are shown below.

Test Set Average


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Sequence 11


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Sequence 12


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Sequence 13


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Sequence 14


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Sequence 15


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