Motion Similarity Modeling -- A State of the Art Report

TL;DR

This report reviews current methods for analyzing and comparing 3D human motions, emphasizing the importance of selecting appropriate similarity measures for specific applications.

Contribution

It provides a comprehensive overview of existing human motion analysis techniques and similarity modeling approaches, highlighting their application contexts and features.

Findings

Summarizes various motion similarity features

Describes approaches for measuring action similarity

Focuses on methods applicable to 3D motion data

Abstract

The analysis of human motion opens up a wide range of possibilities, such as realistic training simulations or authentic motions in robotics or animation. One of the problems underlying motion analysis is the meaningful comparison of actions based on similarity measures. Since the motion analysis is application-dependent, it is essential to find the appropriate motion similarity method for the particular use case. This state of the art report provides an overview of human motion analysis and different similarity modeling methods, while mainly focusing on approaches that work with 3D motion data. The survey summarizes various similarity aspects and features of motion and describes approaches to measuring the similarity between two actions.