Name
Abstract | ||
|---|---|---|
In recent years, video analysis and event recognition are becoming a popular research topic with wide applications in surveillance and security. In this paper, we proposed a video action appearance modeling based on spatio-temporal graph embedding and video action recognition based on video luminance field trajectory spline modeling and aligned matching. Graphs are computed from spline re-sampling of training video data set. Matching is achieved from minimizing the average projection distance between query clips and training groups. Simulation with the Cambridge hand gesture data set demonstrates the effectiveness of the proposed solution. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICASSP.2010.5496275 | 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING |
Keywords | Field | DocType |
Appearance modeling, Graph Embedding, Spline Modeling, Video Event Analysis | Spline (mathematics),Graph theory,Computer vision,Pattern recognition,Computer science,Graph embedding,Gesture,Action recognition,Video tracking,Artificial intelligence,Luminance,Trajectory | Conference |
ISSN | Citations | PageRank |
1520-6149 | 4 | 0.40 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yin Yuan | 1 | 4 | 0.40 |
| Haomian Zheng | 2 | 9 | 2.61 |
| Zhu Li | 3 | 940 | 82.17 |
| David Zhang | 4 | 7365 | 360.85 |