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...
| Κύριος συγγραφέας: | |
|---|---|
| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2010.
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| Σειρά: | Springer Tracts in Advanced Robotics,
64 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.
