Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints

09/11/2019
by   Carlos Caetano, et al.
5

In the last years, the computer vision research community has studied on how to model temporal dynamics in videos to employ 3D human action recognition. To that end, two main baseline approaches have been researched: (i) Recurrent Neural Networks (RNNs) with Long-Short Term Memory (LSTM); and (ii) skeleton image representations used as input to a Convolutional Neural Network (CNN). Although RNN approaches present excellent results, such methods lack the ability to efficiently learn the spatial relations between the skeleton joints. On the other hand, the representations used to feed CNN approaches present the advantage of having the natural ability of learning structural information from 2D arrays (i.e., they learn spatial relations from the skeleton joints). To further improve such representations, we introduce the Tree Structure Reference Joints Image (TSRJI), a novel skeleton image representation to be used as input to CNNs. The proposed representation has the advantage of combining the use of reference joints and a tree structure skeleton. While the former incorporates different spatial relationships between the joints, the latter preserves important spatial relations by traversing a skeleton tree with a depth-first order algorithm. Experimental results demonstrate the effectiveness of the proposed representation for 3D action recognition on two datasets achieving state-of-the-art results on the recent NTU RGB+D 120 dataset.

READ FULL TEXT

page 1

page 4

page 5

page 6

page 7

research
07/30/2019

SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition

Due to the availability of large-scale skeleton datasets, 3D human actio...
research
03/24/2016

Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

Skeleton based action recognition distinguishes human actions using the ...
research
07/06/2017

Skeleton-based Action Recognition Using LSTM and CNN

Recent methods based on 3D skeleton data have achieved outstanding perfo...
research
06/26/2017

Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates

Skeleton-based human action recognition has attracted a lot of research ...
research
10/03/2020

A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition

In the last few years, compression of deep neural networks has become an...
research
02/01/2018

A Fusion of Appearance based CNNs and Temporal evolution of Skeleton with LSTM for Daily Living Action Recognition

In this paper, we propose efficient method which combines skeleton infor...
research
04/19/2016

Online Human Action Detection using Joint Classification-Regression Recurrent Neural Networks

Human action recognition from well-segmented 3D skeleton data has been i...

Please sign up or login with your details

Forgot password? Click here to reset