creating a bag of features for new image set for monocular SLAM
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Hi,
I am interested in visual SLAM. I have taken the example project from "Monocular Visual Simultaneous Localization and Mapping" and have been able to run it with the specified dataset. If I want to run with a different dataset (KITTI), what is the process for setting up the data? I believe I need to create a bag of features off-line? Is that correct? How exactly is that done. It is not explained well in the example.
In the example, a mat is loaded here: I was able to use the bagOfFeaturesDataSLAM.mat file from the example.
% Load the bag of features data created offline
bofData = load("bagOfFeaturesDataSLAM.mat");
For a new data set, you would need to create a new file, correct? That is not obvious to me what that procedure is.
thank you
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Qu Cao
2022년 10월 20일
The bag-of-features data may not work for the KITTI dataset because it was trained using a small amount of image data. You may want to built your own bag-of-features bag following this section of the example.
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Qu Cao
2022년 10월 21일
편집: Qu Cao
2022년 10월 21일
If you want to run the pipeline on a different dataset, you may want to tune some of the parameters. For example, you may want to increase the numbers of feature points extracted from each image because the image resolution in the KITTI dataset is much larger than the one used in the example (480x640). Also, the frame rate of KITTI dataset is 10Hz, so you want to decrase the maximum skipped frame numSkipFrames to a smaller value, say 5.
For your convenience, I've attached a updated main example file for you. Note that you need to define your path to the image data and the camera intrinsic parameters.
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