Paper Info
Title
Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm
Abstract
The general ability to analyze and classify the 3D kinematics of the human form is an essential step in the development of socially adept humanoid robots. A variety of different types of signals can be used by machines to represent and characterize actions such as RGB videos, infrared maps, and optical flow. In particular, skeleton sequences provide a natural 3D kinematic description of human motions and can be acquired in real time using RGB+D cameras. Moreover, skeleton sequences can be generalized to characterize the motions of both humans and humanoid robots. The Globally Optimal Reparameterization Algorithm (GORA) is a novel, recently proposed algorithm for signal alignment in which signals are reparameterized to a globally optimal universal standard timescale (UST). Here, we introduce a variant of GORA for humanoid action recognition with skeleton sequences, which we call GORA-S. We briefly review the algorithm's mathematical foundations and contextualize them in the problem of action recognition with skeleton sequences. Subsequently, we introduce GORA-S and discuss parameters and numerical techniques for its effective implementation. We then compare its performance with that of the DTW and FastDTW algorithms, in terms of computational efficiency and accuracy in matching skeletons. Our results show that GORA-S attains a complexity that is significantly less than that of any tested DTW method. In addition, it displays a favorable balance between speed and accuracy that remains invariant under changes in skeleton sampling frequency, lending it a degree of versatility that could make it well-suited for a variety of action recognition tasks.
Year
DOI
Venue
2018
10.1109/HUMANOIDS.2018.8624999
2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)
Keywords
DocType
Volume
GORA-S,skeleton sampling frequency,action recognition tasks,signal alignment,humanoid skeletons,socially adept humanoid robots,RGB videos,skeleton sequences,natural 3D kinematic description,human motions,RGB+D cameras,globally optimal universal standard timescale,humanoid action recognition,globally optimal reparameterization algorithm,infrared maps,optical flow
Conference
abs/1807.07432
ISSN
ISBN
Citations 
2164-0572
978-1-5386-7284-6
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Thomas W. Mitchel112.05
Sipu Ruan212.73
Gregory Chirikjian31087124.75