Dynamic 3D Mapping - Visual Estimation of Independent Motions for 3D Structures in Dynamic Environments

Juan Carlos Ramirez, Darius Burschka

Abstract

This paper describes an approach to consistently model and characterize potential object candidates presented in non-static scenes. With a stereo camera rig we recollect and collate range data from different views around a scene. Three principal procedures support our method: i) the segmentation of the captured range images into 3D clusters or blobs, by which we obtain a first gross impression of the spatial structure of the scene, ii) the maintenance and reliability of the map, which is obtained through the fusion of the captured and mapped data to which we assign a degree of existence (confidence value), iii) the visual motion estimation of potential object candidates, through the combination of the texture and 3D-spatial information, allows not only to update the state of the actors and perceive their changes in a scene, but also to maintain and refine their individual 3D structures over time. The validation of the visual motion estimation is supported by a dual-layered 3Dmapping framework in which we are able to store the geometric and abstract properties of the mapped entities or blobs, and determine which entities were moved in order to update the map to the actual scene state.

References

  1. Arun, K. S., Huang, T. S., and Blostein, S. D. (1987). Leastsquares fitting of two 3-d point sets. IEEE Trans. Pattern Anal. Mach. Intell., 9(5):698-700.
  2. Kitt, B., Geiger, A., and Lategahn, H. (2010). Visual odometry based on stereo image sequences with ransacbased outlier rejection scheme. In Intelligent Vehicles Symposium (IV), 2010 IEEE, pages 486 -492.
  3. Lin, K.-H. and Wang, C.-C. (2010). Stereo-based simultaneous localization, mapping and moving object tracking. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages 3975 - 3980.
  4. Moosmann, F. and Fraichard, T. (2010). Motion estimation from range images in dynamic outdoor scenes. In Robotics and Automation (ICRA), 2010 IEEE International Conference on, pages 142 -147.
  5. Nister, D., Naroditsky, O., and Bergen, J. (2004). Visual odometry. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, volume 1, pages I652 - I-659 Vol.1.
  6. Ramirez, J. and Burschka, D. (2011). Framework for consistent maintenance of geometric data and abstract task-knowledge from range observations. In Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on. To be published.
  7. Wang, C.-C., Thorpe, C., and Thrun, S. (2003). Online simultaneous localization and mapping with detection and tracking of moving objects: theory and results from a ground vehicle in crowded urban areas. In Robotics and Automation, 2003. Proceedings. ICRA 7803. IEEE International Conference on, volume 1, pages 842 - 849 vol.1.
  8. Wang, Y.-T., Feng, Y.-C., and Hung, D.-Y. (2011). Detection and tracking of moving objects in slam using vision sensors. In Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE, pages 1 -5.
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Paper Citation


in Harvard Style

Ramirez J. and Burschka D. (2013). Dynamic 3D Mapping - Visual Estimation of Independent Motions for 3D Structures in Dynamic Environments . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 402-406. DOI: 10.5220/0004288004020406


in Bibtex Style

@conference{visapp13,
author={Juan Carlos Ramirez and Darius Burschka},
title={Dynamic 3D Mapping - Visual Estimation of Independent Motions for 3D Structures in Dynamic Environments},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={402-406},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004288004020406},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Dynamic 3D Mapping - Visual Estimation of Independent Motions for 3D Structures in Dynamic Environments
SN - 978-989-8565-48-8
AU - Ramirez J.
AU - Burschka D.
PY - 2013
SP - 402
EP - 406
DO - 10.5220/0004288004020406