Write Python algorithm for 3D data


I need someone to implement the Canonical Time Warping algorithm in Python (or your preferred language), as specified in this research paper: [login to view URL]~ftorre/Fernando%20De%20la%20Torre_files/publications_files/[login to view URL]

Here is the problem I have:

I have 3D data points representing the joints of humans for 5-seconds of movement. For example, the data points correspond to the elbows or the knees or the hips during 5-seconds of punching in 3D coordinates.

I need someone to implement the algorithm in the paper so that if I give the function 2 sets of 3D time series data, the algorithm will optimally align the data. For example, by giving the function movement data for person A and movement data for person B (who have both done 3 punches in the 5 seconds), then the model will optimally align the punching movements so that they closely align in time.

This involves Dynamic Time Warping (DTW) and Canonical Correlation Analysis (CCA). Once you have these concepts down I think the algorithm should be easy to implement, because I believe the algorithm from the paper is just a loop of DTW and CCA until you get to low enough error.

I believe the authors have a GitHub repo of this algorithm, but I don't want to use that because there's no commercial license, and it's not in Python.

If you are interested and think you can do this, then please let me know how much time you think this would take.



Skills: Python, Software Architecture, Mathematics

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