Name
Title | ||
|---|---|---|
Prediction Of Multi-Target Dynamics Using Discrete Descriptors: An Interactive Approach |
Abstract | ||
|---|---|---|
We propose a probabilistic method to track and interpret the interactions of moving objects. The proposed method is based on the analysis of location data from different moving objects that modify their dynamics according to rules of interactions, namely attractive and repulsive forces governing objects' motions in a scene. Our method uses a Bayesian structure to identify key elements of the interplay rules and facilitates the prediction of objects' dynamics as an interacting system. Such a prediction facilitates the detection of abnormalities by identifying unseen interaction effects in the scene. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/icassp.2019.8682272 | 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Abnormality detection, interacting models, trajectory analysis, Kalman filter, Particle filter | Pattern recognition,Computer science,Probabilistic method,Location data,Artificial intelligence,Bayesian probability | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamad Baydoun | 1 | 9 | 5.23 |
| Damian Campo | 2 | 16 | 6.41 |
| Divya Kanapram | 3 | 0 | 0.34 |
| Lucio Marcenaro | 4 | 401 | 66.21 |
| Carlo Regazzoni | 5 | 140 | 14.15 |