Name
Abstract | ||
|---|---|---|
Human action recognition using depth-map images from 3D camera for surveillance system is a promising alternative to the conventional 2D video based surveillance. We propose a security-event detection method based on body part classification and human action recognition for more effective video surveillance system. Experimental results show that the body part classification accuracy of 65.0% and security event detection accuracy of 0.878 were achieved for 9 security events. |
Year | Venue | Field |
|---|---|---|
2018 | ICUFN | Computer vision,3d camera,Computer science,Action recognition,Artificial intelligence,Distributed computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungjoo Park | 1 | 0 | 2.70 |
| Dongchil Kim | 2 | 0 | 2.03 |