Information about the example vocabulary #40
Description
Hello @rmsalinas @shinsumicco ,
When creating my own vocabulary I noticed that the weight of all nodes is the same (1) and that creating a BoW vector just counts the number of appearances (no tf or idf).
Using the data set the example vocab is apparently based on (Bovisa_2008-09-01) and taking a closer look at the resulting BoW Vectors, I tried to replicate the performance of the example vocab but was not able to get similar results For the vocabulary given in the vocabularies folder there seems to be some kind of weighting included.
For this reason, I wanted to ask how the example vocabulary was created (e.g. using fbow or by converting some existing vocab into fbow format) and what kind of weighting technique was used.
Adding this information would be helpful for anyone wanting to build their own vocabularies.
Information that would be helpful:
- Which tool was used to create the vocabulary (fbow, dbow2/3, something else?)
- Which image data set has been used and what was its resolution?
- Have all images of this dataset been used or e.g. only every nth image?
- How many keypoints have been extracted per image (500, 2000?)
- How was the vocabulary size of K10L6 determined? Is there a good approach to come up with a well-suited vocabulary size?
- Which weighting technique was used to give the words different weights?
Thank you very much in advance!