Trajectory Similarity Measures
Create an Average Point Translation Vector
Check if Two Points Lie Within some Distance in All Dimensions
Calculate the Square Distance Between Two Points
Calculate the Dot Product Between Two Vectors
Run the Dynamic Time Warping Algorithm on Two Trajectories
Run the Edit Distance Algorithm on Two Trajectories
Run the Frechet Calculation Algorithm on Two Trajectories
Checks a Frechet Leash Distance
Run the LCSS Algorithm on Two Trajectories Allowing Translations
Run the LCSS Algorithm on Two Trajectories Without Translations
Find the LCSS Ratio using Two Trajectories Allowing Translations
Find the LCSS Ratio using Two Trajectories Without Translations
Create a Translation Vector Using LCSS
Implements Several Similarity Measures and Useful Functions
Loop Over and Test Trajectories With Different Translations
Calculate Frechet Distance With a Single Point Trajectory
Translate a Trajectory Based on Start and End Points
Checking Two Trajectories are Matrices of N Dimensional Points
Calculate the Subset of Translations for LCSS
Functions to run and assist four different similarity measures. The similarity measures included are: longest common subsequence (LCSS), Frechet distance, edit distance and dynamic time warping (DTW). Each of these similarity measures can be calculated from two n-dimensional trajectories, both in matrix form.