-
Notifications
You must be signed in to change notification settings - Fork 4
/
Copy pathREADME.txt
31 lines (22 loc) · 1.17 KB
/
README.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
This code is implementation of the following paper:
Xikang Zhang, Yin Wang, Mengran Gou, Mario Sznaier, and Octavia Camps: Efficient Temporal Sequence Comparison and Classification using Gram Matrix Embeddings On a Riemannian Manifold, CVPR 2016
Project website page:
http://robustsystems.coe.neu.edu/sites/robustsystems.coe.neu.edu/files/systems/projectpages/cvpr16gram.html
Prerequisites:
MSR3dAction and UTKinect datasets are with this code. But for the datasets MHAD and HDM05, you need to download by yourself before you can use them. The download websites are:
HDM05 (http://resources.mpi-inf.mpg.de/HDM05)
MHAD (http://tele-immersion.citris-uc.org/berkeley_mhad)
The parser code for HDM05 is:
GramRiemannian/matlab/dataGeneration/parseHDM05.m
The parser code for MHAD datasets is:
GramRiemannian/skeleton_data/MHAD/parseMHAD.m
You need to set up the correct path before running the parser code.
The main function “skeletal_action_classification.m” is in the folder “matlab”. It is used in the following way:
% skeletal_action_classification(dataset_idx)
% dataset_idx is set:
% 1 if UTKinect
% 2 if MHAD
% 3 if MSRAction3D
% 4 if HDM05
Author:
Xikang Zhang ([email protected])