Real time complex scene segmentation and prediction in urban environments
Lead Research Organisation:
University of Surrey
Department Name: Vision Speech and Signal Proc CVSSP
Abstract
Real time complex scene segmentation and prediction in urban environments The project will be looking at
spatiotemporal sematic segmentation and prediction of actions of other road users in the context of SAE level 4-5
autonomous vehicles. But specifically, it will focus on inner city/urban driving. It will focus on the computer vision tools for
segmentation and reasoning about scene content and motion with integration into ROS and testing on our autonomous
testbed.
spatiotemporal sematic segmentation and prediction of actions of other road users in the context of SAE level 4-5
autonomous vehicles. But specifically, it will focus on inner city/urban driving. It will focus on the computer vision tools for
segmentation and reasoning about scene content and motion with integration into ROS and testing on our autonomous
testbed.
People |
ORCID iD |
Richard Bowden (Primary Supervisor) | |
Avishkar Saha (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/T517616/1 | 30/09/2019 | 29/09/2025 | |||
2327211 | Studentship | EP/T517616/1 | 01/01/2020 | 31/12/2023 | Avishkar Saha |