AdaPT: Real-time adaptive pedestrian tracking for crowded scenes
| Autor: | Dinesh Manocha, Adam T. Lake, Aniket Bera, Nico Galoppo, Dillon Sharlet |
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| Rok vydání: | 2014 |
| Předmět: |
Scheme (programming language)
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Probabilistic logic Tracking system Pedestrian Tracking (particle physics) Motion (physics) Computer Science::Multiagent Systems Trajectory Computer vision Artificial intelligence business computer ComputingMethodologies_COMPUTERGRAPHICS computer.programming_language |
| Zdroj: | ICRA |
| DOI: | 10.1109/icra.2014.6907095 |
| Popis: | We present a novel realtime algorithm to compute the trajectory of each pedestrian in a crowded scene. Our formulation is based on an adaptive scheme that uses a combination of deterministic and probabilistic trackers to achieve high accuracy and efficiency simultaneously. Furthermore, we integrate it with a multi-agent motion model and local interaction scheme to accurately compute the trajectory of each pedestrian. We highlight the performance and benefits of our algorithm on well-known datasets with tens of pedestrians. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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