Capturing Global and Local Dynamics for Human Action Recognition

By Siqi Nie, Qiang Ji. 2014

31 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Vittorio Murino
2. Pietro Morerio
3. Jacopo Cavazza
4. Zhiwu Huang
5. Luc Van Gool
6. Thomas Probst
7. Chengde Wan
8. Xiaogang Wang

In Control and Systems Engineering

1. Zhiwu Huang
2. Luc Van Gool
3. Vittorio Murino
4. Thomas Probst
5. Pietro Morerio
6. Chengde Wan
7. Jacopo Cavazza

Citations in the corpus

• When Kernel Methods Meet Feature Learning: Log-Covariance Network for Action Recognition From Skeletal Data (2017, methodology): “Comparative analysis We benchmarked with [26] which combined Restricted Boltzmann machines and Hidden Markov Models.”
• Deep Learning on Lie Groups for Skeleton-Based Action Recognition (2016, methodology): “Table 1 compares the proposed LieNet with the state-of-the-art methods (i.e., RBM-HMM [31], SE [40] and SO [41]) reported for the G3D-Gaming dataset.”
• Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data (2016, unknown): “RBM + HMM [16] 86.”