Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms

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...

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Bibliographic Details
Main Author: Geiger, Andreas (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2013
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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020 |a KSP/1000036064 
020 |a 9783731500810 
024 7 |a 10.5445/KSP/1000036064  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Geiger, Andreas  |4 auth 
245 1 0 |a Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms 
260 |b KIT Scientific Publishing  |c 2013 
300 |a 1 electronic resource (V, 162 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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. 
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546 |a English 
653 |a computer vision 
653 |a machine learning 
653 |a scene understanding 
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