Context models for pedestrian intention prediction by factored latent-dynamic conditional random fields
Smooth handling of pedestrian interactions is a key requirement for Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS). Such systems call for early and accurate prediction of a pedestrian's crossing/not-crossing behaviour in front of the vehicle. Existing approaches to pedes...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/143222 |
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| Institution: | Nanyang Technological University |
| Language: | English |