Name
Title | ||
|---|---|---|
Efficient human action recognition by luminance field trajectory and geometry information |
Abstract | ||
|---|---|---|
In recent years the video event understanding is an active research topic, with many applications in surveillance, security, and multimedia search and mining. In this paper we focus on the human action recognition problem and propose a new Curve-Distance approach based on the geometry modeling of video appearance manifold and the human action time series statistics on the geometry information. Experimental results on the KTH database demonstrate the solution to be effective and promising. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICME.2009.5202626 | ICME |
Keywords | Field | DocType |
human action recognition problem,kth database,video signal processing,geometry information,pattern recognition,video event recognition,active research topic,human action time series statistics,efficient human action recognition,curve-distance approach,human action recognition,multimedia search,geometry modeling,machine learning,video event understanding,luminance field trajectory,time series,human action time series,video appearance manifold,indexing terms,shape,trajectory,geometry,data mining | Computer vision,Multimedia search,Pattern recognition,Computer science,Action recognition,Artificial intelligence,Geometry,Luminance,Trajectory,Machine learning,Manifold | Conference |
ISSN | ISBN | Citations |
1945-7871 E-ISBN : 978-1-4244-1291-1 | 978-1-4244-1291-1 | 2 |
PageRank | References | Authors |
0.36 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haomian Zheng | 1 | 9 | 2.61 |
| Zhu Li | 2 | 940 | 82.17 |
| Yun Fu | 3 | 4267 | 208.09 |