Feature extraction in machine learning
I don't know much but maybe my answer would helps you. For machine learning, we have to do feature engineering to extract the important features from the data. Here we have images and the methods above to extract features of each object and image, then classify them using one of machine learning algorithms.
In CNNs, you do all these together and that's why the the CNNs object detection approach is better than ML approaches.
If you look at any of famous object detection models, you will see a CNN model such as ResNet or VGG which are used for feature extraction as a first part of the model.
Also, you can use the model for feature extractions and then apply ML algorithms to classify such as KNN, SVM, etc.