1 / 8

The Stixel World – A Compact Medium Level Representation of the 3D-World

The Stixel World – A Compact Medium Level Representation of the 3D-World. Hernan Badino , Uwe Franke , and David Pfeiffer Daimer AG DAGM 2009 Presenter: Jonghee Park GIST CV-Lab. Introduction. Stereo vision play an essential role for scene understanding in cars of the near future

ham
Télécharger la présentation

The Stixel World – A Compact Medium Level Representation of the 3D-World

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The Stixel World – A Compact Medium Level Representation of the 3D-World Hernan Badino, UweFranke, and David Pfeiffer Daimer AG DAGM 2009 Presenter: Jonghee Park GIST CV-Lab.

  2. Introduction • Stereo vision play an essential role for scene understanding in cars of the near future • SGM • Three out of ten most powerful stereo is SGM variants in Middlebury dataset • Implement using FPGA • Extract and track every object • Use multiple object detectors • Repetitively evaluate images • Incomplete detection

  3. Introduction • Requirements of automotive environment perception and modeling • Compact • Reduction of the data volume • Complete • Information of interest is preserved • Stable • Small changes of the underlying data must not cause rapid changes within the representation • Robust • Outliers must have minimal

  4. Free space • Occupancy Grid • Two dimensional grid which models occupancy evidence of the environments • Only 3D measurements lying above the road are registered • Free space computation [1] • The space found in front of the occupied cell is considered free space • Bottom of the obstacles is obtained from the free space [1] Hern´an Badino, Uwe Franke, Rudolf Mester, Free Space Computation Using Stochastic Occupancy Grids and Dynamic Programming, ICCV workshop 2007

  5. Height Segmentation • The height of the obstacles is obtained by finding the optimal segmentation between foreground and background • Membership value • Depth difference between disparity • : bottom point set from free space analysis • : X,Z world position corresponding to • : set to 2 meter

  6. Height Segmentation • Cost image from membership value • Accumulate from top to bottom • : the row position of lies on the road

  7. Height Segmentation • Solve using dynamic programming • : 5m : possible same object depth • : 8 Smoothness term

  8. Result • 25 ms on Intel Quad Core 3.00 GHz

More Related