… linear dynamical system (tLDS) for modeling tensor observations in time series and employed
Tucker decomposition to estimate the parameters of the LDS model as action descriptors. …

… a series of simulation experiments and analyses using two publicly available skeleton-based
action recognition datasets: MSR-Action 3D (MSRA3D) [55] and Florence3D-Action (…

… and action recognition from those images through machine learning algorithms. A time series
of … Camps, “Hankelet-based dynamical systems modeling for 3d action recognition”, Image …

… recognition … of action recognition, in particular, when 3D skeleton joints are considered
as multivariate time-series. Randomly fixed neuron weights may diversify the recognition …

… 2 s-AGCN is a graph convolutional neural network model used for action recognition.
This model has a dual stream structure, with one stream used to process spatial features (J-stream) …

… of S-ConvESN is evaluated using several 3Dskeleton-based action recognition datasets. …
Sclaroff, and O, Camps, Hankelet-based dynamical systems modeling for 3d action recognition. …

… Section 3 introduces the technical material for this article, overviewing dynamical systems,
autoencoders and the temporal sequence that we use for diagnostics input. Section 4 defines …

… Ijjina, EP, Mohan, CK: Human action recognition based on mocap information using
convolution neural networks. In: 2014 13th International Conference on Machine Learning and …

… the model, we use the cross-dataset evaluation model [40]. In this paper, we use the model
on … for 2D-3D mapping, and our model has strong generalization ability for unknown scenes. …

… This study is about real-time 2D-3D human pose estimation without using the a priori …
model a 3D human skeleton with high-precision, it can be used to understand human action …