Notice: Forked from paalel/Signatures-in-Shape-Analysis. This fork exists so that paalel/Signatures-in-Shape-Analysis can be used with python3 and installed via pip. Some other minor changes were made to enable plotting of the value matrix.

To install the package, download it, and make the database as described below. Then install the package with

pip3 install -e . 

from the package root.

The animation folder contains two subfolders: src and db. src/ contains all things animation related, that is Skeleton and Animation objects, methods for parsing .asf/.amc-files, methods for creating animations and some attempts at different frame interpolation.

db/ contains data and our database. To create the tables run:

sqlite3 <Name_of_db>.db < create_tables_sqlite3.sql

unzip the mocap data from mocap.cs.cmu.edu

create config-file: cp db_config_example.py db_config.py

and add the paths to your database and subject folder.

run:

python insert_data_db_sqllite3.py

to add data to database and download subject descriptions (which are scattered all over the site) from mocap.cs.cmu.edu

animation_manager.py is an interface for fetching animations in applications

The folder so3/ contains implementation our mathematical framework for SO3.

convert.py : convert animation to curce in SO3

transformations.py log, exp, interpolate, SRVT and other transformations applied to SO3 or curves in SO3

curves.py: operations that take a curve, or multiple curves as parameters. This includes distance, dynamic_distance, close, move_origin and others. These are all written to be quite functional, note however that python has no way of actually enforcing this.

dynamic_distance.py: implementations off the the dynamic distance method proposed by Bauer.

signature.py and log_signature.py: proposed metrics using the iisignature library.

experiments, test, and clustering all contain different applications of these method