Name
Abstract | ||
|---|---|---|
We propose an approach to recognize group activities which involve several persons based on modeling the interactions between human bodies. Benefitted from the recent progress in pose estimation [1], we model the activities as the interactions between the parts belong to the same person (intra-person) and those between the parts of different persons (inter-person). Then a unified, discriminative model which integrates both types of interactions is developed. The experiments on the UT-Interaction Dataset [2] show the promising results and demonstrate the power of the interacting models. |
Year | Venue | Keywords |
|---|---|---|
2012 | ICPR | semantic spatial relation,unified discriminative model,pose estimation,ut-interaction dataset,human activity recognition,group activity recognition,activity modeling,interaction modeling |
Field | DocType | ISSN |
Spatial relation,Computer vision,Activity recognition,Pattern recognition,Computer science,Pose,Artificial intelligence,Discriminative model,Machine learning | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 7 | 0.46 |
References | Authors | |
13 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingxun Meng | 1 | 7 | 0.46 |
| Laiyun Qing | 2 | 337 | 24.66 |
| Peng Yang | 3 | 112 | 4.57 |
| Jun Miao | 4 | 220 | 22.17 |
| Xilin Chen | 5 | 6291 | 306.27 |
| Dimitris N. Metaxas | 6 | 8834 | 952.25 |