Name
Abstract | ||
|---|---|---|
This paper introduces a new method for human action recognition based on human body skeleton. The proposed method is composed of two phases: an off-line phase which selects the most discriminant human body regions and an online phase to classify the request action. In both phases, we applied the cumulative skeletonized images matrix to extract the action features. The experimental study shows that the proposed method, thanks to salient regions selection and the two-level classification strategy, provides good results comparable in terms of recognition accuracy to the most known and recent state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11760-017-1227-z | Signal, Image and Video Processing |
Keywords | Field | DocType |
Human action recognition, Cumulative skeletonized images, mRMR, SVM | Request - action,Pattern recognition,Discriminant,Matrix (mathematics),Action recognition,Support vector machine,Artificial intelligence,Body Regions,Mathematics,Salient | Journal |
Volume | Issue | ISSN |
12 | 5 | 1863-1703 |
Citations | PageRank | References |
1 | 0.35 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mliki Hazar | 1 | 11 | 4.91 |
| Rabàa Zaafouri | 2 | 1 | 0.35 |
| Mohamed Hammami | 3 | 181 | 30.54 |