Recognizing Human Actions Using NWFE-Based Histogram Vectors
This study presents a novel system for human action recognition. Two research issues, namely, motion representation and subspace learning, are addressed. In order to have a rich motion descriptor, we propose to combine the distance signal and the width feature so that a silhouette can be characteriz...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2010-01-01
|
| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2010/453064 |
| _version_ | 1811280124470886400 |
|---|---|
| author | Cheng-Hsien Lin Fu-Song Hsu Wei-Yang Lin |
| author_facet | Cheng-Hsien Lin Fu-Song Hsu Wei-Yang Lin |
| author_sort | Cheng-Hsien Lin |
| collection | DOAJ |
| description | This study presents a novel system for human action recognition. Two research issues, namely, motion representation and subspace learning, are addressed. In order to have a rich motion descriptor, we propose to combine the distance signal and the width feature so that a silhouette can be characterized in more detail. These two features provide complementary information and are integrated to yield a better discriminative power. The combined features are subsequently quantized into mid-level features using k-means clustering. In the mid-level feature space, we apply the Nonparametric Weighted Feature Extraction (NWFE) to construct a compact yet discriminative subspace model. Finally, we can simply train a Bayes classifier for recognizing human actions. We have conducted a series of experiments on two publicly available datasets to demonstrate the effectiveness of the proposed system. Compared with the existing approaches, our system has a significantly reduced complexity in classification stage while maintaining high accuracy. |
| first_indexed | 2024-04-13T01:07:50Z |
| format | Article |
| id | doaj.art-98638d5dee034f6da4262e847c18f433 |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-04-13T01:07:50Z |
| publishDate | 2010-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-98638d5dee034f6da4262e847c18f4332022-12-22T03:09:16ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802010-01-01201010.1155/2010/453064Recognizing Human Actions Using NWFE-Based Histogram VectorsCheng-Hsien LinFu-Song HsuWei-Yang LinThis study presents a novel system for human action recognition. Two research issues, namely, motion representation and subspace learning, are addressed. In order to have a rich motion descriptor, we propose to combine the distance signal and the width feature so that a silhouette can be characterized in more detail. These two features provide complementary information and are integrated to yield a better discriminative power. The combined features are subsequently quantized into mid-level features using k-means clustering. In the mid-level feature space, we apply the Nonparametric Weighted Feature Extraction (NWFE) to construct a compact yet discriminative subspace model. Finally, we can simply train a Bayes classifier for recognizing human actions. We have conducted a series of experiments on two publicly available datasets to demonstrate the effectiveness of the proposed system. Compared with the existing approaches, our system has a significantly reduced complexity in classification stage while maintaining high accuracy.http://dx.doi.org/10.1155/2010/453064 |
| spellingShingle | Cheng-Hsien Lin Fu-Song Hsu Wei-Yang Lin Recognizing Human Actions Using NWFE-Based Histogram Vectors EURASIP Journal on Advances in Signal Processing |
| title | Recognizing Human Actions Using NWFE-Based Histogram Vectors |
| title_full | Recognizing Human Actions Using NWFE-Based Histogram Vectors |
| title_fullStr | Recognizing Human Actions Using NWFE-Based Histogram Vectors |
| title_full_unstemmed | Recognizing Human Actions Using NWFE-Based Histogram Vectors |
| title_short | Recognizing Human Actions Using NWFE-Based Histogram Vectors |
| title_sort | recognizing human actions using nwfe based histogram vectors |
| url | http://dx.doi.org/10.1155/2010/453064 |
| work_keys_str_mv | AT chenghsienlin recognizinghumanactionsusingnwfebasedhistogramvectors AT fusonghsu recognizinghumanactionsusingnwfebasedhistogramvectors AT weiyanglin recognizinghumanactionsusingnwfebasedhistogramvectors |