Abstract
This paper presents a pedestrian trajectory prediction technique. Its mail novelty is that it does not require any previous observation or knowledge of pedestrian trajectories, thus making it useful for autonomous surveillance applications. The prediction requires only a set of possible goals, a map of the scenario and the initial position of the pedestrian. Then, it uses two different path planing algorithms to find the possible routes and transforms the similarity between observed and planned routes into probabilities. Finally, it applies a motion model to obtain a time-stamped predicted trajectory. The system has been used in combination with a pedestrian detection and tracking system for real-world tests as well as a simulation software for a large number of executions.
Original language | English |
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Title of host publication | ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics |
Editors | Oleg Gusikhin, Dimitri Peaucelle, Kurosh Madani |
Publisher | SciTePress |
Pages | 381-389 |
ISBN (Electronic) | 9789897581984 |
DOIs | |
Publication status | Published - 2016 |
Externally published | Yes |
Event | 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 - Lisbon, Portugal Duration: 29 Jul 2016 → 31 Jul 2016 |
Conference
Conference | 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 |
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Country/Territory | Portugal |
City | Lisbon |
Period | 29/07/16 → 31/07/16 |
Keywords
- Pedestrian trajectory prediction
- Planning-based prediction
- Trajectory forecast