Improve this project with RNN (LSTM) about realtime-action-recognition

[felixchenfy]

You may check the Trouble shooting: section in README. Basically, you need to read the code, find the files that define the feature and model, and then change them. It will be lots of changes. Sorry about that.

I copied it here for your convinience:

Trouble shooting:

• How to change features?

  In utils/lib_feature_proc.py, in the class FeatureGenerator, change the function def add_cur_skeleton!

  The function reads in a raw skeleton and outputs the feature generated from this raw skeleton as well as previous skeletons. The feature will then be saved to features_X.csv by the script s3_preprocess_features.py for the next training step.

• How to include joints of the head?

  You need to change the aforementioned add_cur_skeleton function.

  I suggest you to write a new function to extract the head features, and then append them to the returned variable(feature) of add_cur_skeleton.

  Please read def retrain_only_body_joints in utils/lib_feature_proc.py if you want to add the head joints.

• How to change the classifier to RNN?

  There are two major changes to do:

  First, change the aforementioned add_cur_skeleton. Instead of manually extracing time-serials features as does by the current script, you may simply stack the input skeleton with previous skeletons and then output it.

  Second, change the def __init__ and def predict function of class ClassifierOfflineTrain in utils/lib_classifier.py to add an RNN model.

[Yorkzhang19961122]

thank you for your reply：）

[athulvingt]

have u tried it with LSTM @Yorkzhang19961122