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Incremental Learning for Motion Prediction of Pedestrians and Vehicles

Modeling and predicting human and vehicle motion is an active research domain. Owing to the difficulty in modeling the various factors that determine motion (e.g. internal state, perception) this is often tackled by applying machine learning techniques to build a statistical model, using as input a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Vasquez Govea, Alejandro Dizan (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Springer Tracts in Advanced Robotics, 64
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • I: Background
  • Probabilistic Models
  • II: State of the Art
  • Intentional Motion Prediction
  • Hidden Markov Models
  • III: Proposed Approach
  • Growing Hidden Markov Models
  • Learning and Predicting Motion with GHMMs
  • IV: Experiments
  • Experimental Data
  • Experimental Results
  • V: Conclusion
  • Conclusions and Future Work.