Behavioral Landmarks: Inferring Interactions from Data

Abstract
We aim to unravel complex agent-environment interactions from trajectories, by explaining agent paths as combinations of predefined basic behaviors. We detect trajectory points signifying environment-driven behavior changes, ultimately disentangling interactions in space and time; our framework can be used for environment synthesis and authoring, shown by our case studies.
Description

CCS Concepts: Computing methodologies → Image representations; Neural networks; Motion processing

        
@inproceedings{
10.2312:egp.20241039
, booktitle = {
Eurographics 2024 - Posters
}, editor = {
Liu, Lingjie
and
Averkiou, Melinos
}, title = {{
Behavioral Landmarks: Inferring Interactions from Data
}}, author = {
Lemonari, Marilena
and
Charalambous, Panayiotis
and
Panayiotou, Andreas
and
Chrysanthou, Yiorgos
and
Pettré, Julien
}, year = {
2024
}, publisher = {
The Eurographics Association
}, ISSN = {
1017-4656
}, ISBN = {
978-3-03868-239-4
}, DOI = {
10.2312/egp.20241039
} }
Citation