Context models for pedestrian intention prediction by factored latent-dynamic conditional random fields

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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書目詳細資料
主要作者:	Satyajit Neogi
其他作者:	Justin Dauwels
格式:	Thesis-Doctor of Philosophy
語言:	English
出版:	Nanyang Technological University 2020
主題:	Engineering::Electrical and electronic engineering
在線閱讀:	https://hdl.handle.net/10356/143222
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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