Moving Object Segmentation Using Optical Flow and Depth Information

@inproceedings{Klappstein2009MovingOS,
  title={Moving Object Segmentation Using Optical Flow and Depth Information},
  author={Jens Klappstein and Tobi Vaudrey and Clemens Rabe and Andreas Wedel and Reinhard Klette},
  booktitle={PSIVT},
  year={2009}
}
This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 38 CITATIONS

Manifold clustering for motion segmentation

VIEW 3 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

A Unified Framework for Mutual Improvement of SLAM and Semantic Segmentation

  • 2019 International Conference on Robotics and Automation (ICRA)
  • 2018
VIEW 1 EXCERPT
CITES METHODS

Continuous stereo camera calibration in urban scenarios

  • 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
  • 2017
VIEW 1 EXCERPT
CITES BACKGROUND

Automatic Generation of 3 D GIFs

VIEW 1 EXCERPT
CITES BACKGROUND

Data fusion of radar and stereo vision for detection and tracking of moving objects

  • 2016 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech)
  • 2016
VIEW 1 EXCERPT
CITES BACKGROUND

Generalized dynamic object removal for dense stereo vision based scene mapping using synthesised optical flow

  • 2016 IEEE International Conference on Image Processing (ICIP)
  • 2016
VIEW 2 EXCERPTS
CITES BACKGROUND

Image Matching for Dynamic Scenes

VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 24 REFERENCES

An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2001
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Design of a hybrid visuoinertial smart sensor

P. Chalimbaud, F. Berry, F. Marmoiton, S. Alizon
  • In Proc. Workshop Integration Vision Inertial Sensors (in conjunction with IEEE Int. Conf. Robotics Automation),
  • 2005
VIEW 1 EXCERPT