Enhanced Sequence Matching for Action Recognition from 3D Skeletal Data

By Hyun-Joo Jung, Ki Sang Hong. 2014

15 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Computer Vision and Pattern Recognition

How researchers see this paper

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

In Artificial Intelligence

1. Fei Han
2. Guillermo Garcia-Hernando
3. William A. Hoff
4. Brian Reily
5. Tae-Kyun Kim
6. Hao Zhang

In Biomedical Engineering

1. Fei Han
2. William A. Hoff
3. Brian Reily
4. Guillermo Garcia-Hernando
5. Tae-Kyun Kim
6. Hao Zhang
7. Jun Liu
8. G. Wang

In Computer Vision and Pattern Recognition

1. Guillermo Garcia-Hernando
2. Fei Han
3. William A. Hoff
4. Brian Reily
5. Tae-Kyun Kim
6. Hao Zhang
7. Jun Liu
8. G. Wang

Citations in the corpus

• Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, background): “[191] Fourier Temporal Pyramid BoW Body Unsup X X X Jung and Hong [192] Elementary Moving Pose BoW Lowlv Dict X X X X Evangelidis et al.”
• Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection (2016, methodology): “[36] proposes a Moving Pose descriptor (MP) using both pose and atomic motion information and then temporally mining key frames using a k-NN aproach in contrast to [12] that uses DTW.”