01634nam 2200349z- 450 9910688420403321202102111000036064(CKB)4920000000101903(oapen)https://directory.doabooks.org/handle/20.500.12854/57007(oapen)doab57007(EXLCZ)99492000000010190320202102d2013 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierProbabilistic Models for 3D Urban Scene Understanding from Movable PlatformsKIT Scientific Publishing20131 online resource (V, 162 p. p.)Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie3-7315-0081-7 This work is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences.computer visionmachine learningscene understandingGeiger Andreasauth1352378BOOK9910688420403321Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms3173961UNINA