Name
Abstract | ||
|---|---|---|
We present a frequency domain analysis technique for modelling and recognizing human periodic movements from moving light displays (MLDs). We model periodic motions by motion templates, that consist of a set of feature power vectors extracted from unidentified vertical component trajectories of feature points. Motion recognition is carried out in the frequency domain, by comparing an observed motion template with pre-stored templates. This method contrasts with common spatio-temporal approaches. The proposed method is demonstrated by some examples of human periodic motion recognition in MLDs. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICPR.2002.1044700 | Pattern Recognition, 2002. Proceedings. 16th International Conference |
Keywords | Field | DocType |
computer vision,frequency-domain analysis,image motion analysis,image recognition,MLD,feature power vectors,frequency domain analysis,human periodic motion recognition,motion templates,moving light displays,unidentified vertical component trajectories | Frequency domain,Periodic function,Computer vision,Motion field,Pattern recognition,Computer science,Motion recognition,Artificial intelligence,Template,Motion estimation,Periodic graph (geometry) | Conference |
Volume | ISSN | ISBN |
1 | 1051-4651 | 0-7695-1695-X |
Citations | PageRank | References |
7 | 0.57 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baihua Li | 1 | 176 | 21.71 |
| H. Holstein | 2 | 79 | 8.21 |