Please help me. OpenCV xfeatures2d: true, but the results seem to be the same even if different feature algorithms are used.

[kuacboss]

rtabmap --version
RTAB-Map: 0.21.5
PCL: 1.10.0
With VTK: 7.1.1
OpenCV: 4.2.0
With OpenCV xfeatures2d: true
With OpenCV nonfree: true
With ORB OcTree: true
With SuperPoint Torch: false
With Python3: false
With FastCV: false
With OpenGV: false
With Madgwick: true
With PDAL: false
With TORO: true
With g2o: true
With GTSAM: true
With Vertigo: true
With CVSBA: false
With Ceres: false
With OpenNI2: true
With Freenect: false
With Freenect2: false
With K4W2: false
With K4A: false
With DC1394: true
With FlyCapture2: false
With ZED: false
With ZED Open Capture: false
With RealSense: false
With RealSense SLAM: false
With RealSense2: true
With MYNT EYE S: false
With DepthAI: false
With libpointmatcher: true
With CCCoreLib: false
With Open3D: false
With OctoMap: true
With GridMap: true
With cpu-tsdf: false
With open chisel: false
With Alice Vision: false
With LOAM: false
With FLOAM: false
With FOVIS: false
With Viso2: false
With DVO: false
With ORB_SLAM: false
With OKVIS: false
With MSCKF_VIO: false
With VINS-Fusion: false
With OpenVINS: false

This is the result of my rtapmap --version

As shown in the photo above, even if various feature algorithms are used, the feature point extraction results are almost similar or the same.

(SURF)

(ORB)

Here is the code I ran:
roslaunch rtabmap_demos demo_robot_mapping.launch args:="--Vis/FeatureType ex_ORB, SIFT, SUFT etc."
rosbag play --clock demo_mapping.bag

I installed it like the code below.

https://github.com/introlab/rtabmap_ros

Experts, please help.. Thank you in advance.

[matlabbe]

You have to change Kp/DetectorStrategy to same value than Vis/FeatureType. Also, if you are using opencv binaries as dependency, you may not have access to all types of features, in that case you should see warnings/errors in the terminal about that.