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  4. 3D Object Trajectory Reconstruction using Instance-Aware Multibody Structure from Motion and Stereo Sequence Constraints
 
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2019
Conference Paper
Title

3D Object Trajectory Reconstruction using Instance-Aware Multibody Structure from Motion and Stereo Sequence Constraints

Abstract
Three-dimensional environment perception is a key element of autonomous driving and driver assistance systems. A common image based approach to determine threedimensional scene information is stereo matching, which is limited by the stereo camera baseline. In contrast to stereo matching based methods, we present an approach to reconstruct three-dimensional object trajectories combining temporal adjacent views for object point triangulation. We track twodimensional object shapes on pixel level exploiting instance aware semantic segmentation techniques and optical flow cues. We apply Structure from Motion (SfM) to object and background images to determine initial camera poses relative to object instances as well as background structures and refine the initial SfM results by integrating stereo camera constraints using factor graphs. We compute object trajectories using stereo sequence constraints of object and background reconstructions. We show qualitative results using publicly available video data of driving sequences. Due to the lack of suitable ground truth, we create a synthetic benchmark dataset of stereo sequences with vehicles in urban environments. Our algorithm achieves an average trajectory error of 0.09 meter using the dataset. The dataset is on our website publicly available.
Author(s)
Bullinger, Sebastian  
Bodensteiner, Christoph  
Arens, Michael  
Stiefelhagen, Rainer  
Mainwork
30th IEEE Intelligent Vehicles Symposium, IV 2019  
Conference
Intelligent Vehicles Symposium (IV) 2019  
Open Access
File(s)
Download (3.04 MB)
Rights
Use according to copyright law
DOI
10.24406/publica-r-404625
10.1109/IVS.2019.8814118
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
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