Spatio-temporal feature extraction and representation for RGB-D human action recognition
By Jiajia Luo, Wei Wang, Hairong Qi. 2014
65 citations recorded by the source corpus.
Subfields: 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 Computer Vision and Pattern Recognition
- Ennio Gambi
- Susanna Spinsante
- Enea Cippitelli
- Sergio Escalera
- Isabelle M Guyon
- Francisco Flórez-Revuelta
- Samuele Gasparrini
- Vassilis Athitsos
Citations in the corpus
- RGB-D-based action recognition datasets: A survey (2016, neutral): “2. CS (2,3,5,7,9 subject training, 1,4,6,8,10 subject test) 3. CS (1,3,5,7,9 subject training, 2,4,6,8,10 subject test) MSRDailyActivity3D [14] 1. τ-test [64] 2. DL-GSGC +TPM [65] 3. 3D joint+CS-MLtp [66] 4. Depth-VSFR [67] 1. 95.63 2. 95 3. 92.5 4. 89.7 1. D,S 2. S 3. C,S 4. D 1. Not given 2. CS (H”
- A discussion on the validation tests employed to compare human action recognition methods using the MSR Action3D dataset (2014, background): “iented 4D Normals for Activity Recognition from Depth Sequences, Oreifej and Liu [8] 2013 - 88.89? Spatio-temporal feature extraction and representation for RGB-D human action recognition, Luo et al. [60] 2014 96.1 90.8 98.33 95.08 93.83? Action Classification with Localityconstrained Linear Coding, ”
- A Human Activity Recognition System Using Skeleton Data from RGBD Sensors (2016, methodology): “Luo et al. [20] proposed a human action recognition framework where the pairwise relative positions of joints and Center-Symmetric Motion Local Ternary Pattern (CS-Mltp) features from RGB are fused both at feature level and at classifier level.”
- Computer Vision and Image Understanding Computer Vision for Assistive Technologies (unknown): “In addition, a novel Center-Symmetric Motion Local Ternary Pattern (CS-Mltp) descriptor has been proposed to capture spatial-temporal features from RGB videos at low computational cost ( Luo et al., 2014 ).”
- Challenges in multimodal gesture recognition (2016, background): “In terms of multimodal approaches for gesture recognition, (Luo et al., 2014) propose a sparse coding-based temporal pyramid matching approach (ScTPM) for feature representation using depth maps.”