E-resources
Peer reviewed
Open access
-
Sajina, Romeo; Ivasic-Kos, Marina
IEEE access, 01/2023, Volume: 11Journal Article
In recent years, multi-person pose forecasting has gained significant attention due to its potential applications in various fields such as computer vision, robotics, sports analysis, and human-robot interaction. In this paper, we propose a novel deep learning model for multi-person pose forecasting called MPFSIR (multi-person pose forecasting and social interaction recognition) that achieves comparable results with state-of-the-art models, but with up to 30 times fewer parameters. In addition, the model includes a social interaction prediction component to model and predict interactions between individuals. We evaluate our model on three benchmark datasets: 3DPW, CMU-Mocap, and MuPoTS-3D, compare it with state-of-the-art methods, and provide an ablation study to analyze the impact of the different model components. Experimental results show the effectiveness of MPFSIR in accurately predicting future poses and capturing social interactions. Furthermore, we introduce the metric MW-MPJPE to evaluate the performance of pose forecasting, which focuses on motion dynamics. Overall, our results highlight the potential of MPFSIR for predicting the poses of multiple people and understanding social dynamics in complex scenes and in various practical applications, especially where computational resources are limited. The code is available at https://github.com/RomeoSajina/MPFSIR.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.