References

HoG

1. This is an Opencv Example with the func to visualize hog structure.

2. CLI Example

3. A Opencv HoG trainer on GitHub

4. Parameters Example on StackOverflow. Caution: we MUST adjust it according to our patch size and other shits.

5. HoG theory basis on learnopencv.com

6. Forum

HoG 3D

HoG 3d feature is implemented by myself. Referencing to:

1. A Spatio-Temporal Descriptor Based on 3D-Gradients

2. Behavior recognition via sparse spatio-temporal features

Regex

1. Python module "re" Documentation

2. Remember separators for EPFL UAV dataset:

    sepa_loc = r"\(((\d*),(.))*(\d*)\)"
    ...
    searchObj = re.search(sepa_loc, line, re.M|re.I|re.S)

XGBoost

Git Demo Repo for Py

1. Example for custom obj func

2. Xgboost python API Manual

3. Xgboost python usage introduction

Trifles on python

Other things

Can try scikit module: sklearn.ensemble.GradientBoostingClassifier() as an alternative.