Name
Title | ||
|---|---|---|
Human Action recognition from depth videos using multi-projection based representation |
Abstract | ||
|---|---|---|
In this paper, a novel method for human action recognition from depth videos is proposed. We project 3D data on to multiple 2D-planes from which dense trajectories features are extracted. In the training stage, for each projection, a classifier is trained using the training data. In the testing stage, for each test video, the multiple trained classifiers are applied and the predicted scores are combined for final decision. We propose a greedy-based method to select a subset of the trained classifiers for optimal combination. Experiments on the MSR Action 3D dataset show that the proposed method outperforms the baseline method that does not use multi-projection-based features. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/MMSP.2015.7340879 | 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP) |
Keywords | Field | DocType |
greedy-based method,feature extraction,multi-projection based representation,depth videos,human action recognition | Training set,Computer vision,Pattern recognition,Computer science,Action recognition,Artificial intelligence,Classifier (linguistics),Machine learning | Conference |
ISSN | Citations | PageRank |
2163-3517 | 0 | 0.34 |
References | Authors | |
13 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chien-Quang Le | 1 | 0 | 1.01 |
| Thanh Duc Ngo | 2 | 82 | 22.24 |
| Duy-dinh Le | 3 | 213 | 38.89 |
| Shin'ichi Satoh | 4 | 2093 | 277.41 |
| Duc Anh Duong | 5 | 112 | 19.65 |